ShapRFECV vs sklearn RFECV¶
In this section we will compare the performance of the model trained on the features selected using the probatus ShapRFECV and the sklearn RFECV.
In order to compare them let's first prepare a dataset, and a model that will be applied:
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%%capture
!pip install probatus
!pip install lightgbm
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!pip install probatus
!pip install lightgbm
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import lightgbm
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from sklearn.datasets import make_classification
from sklearn.feature_selection import RFECV
from sklearn.model_selection import cross_val_score, train_test_split
from probatus.feature_elimination import ShapRFECV
# Prepare train and test data:
X, y = make_classification(
n_samples=10000, class_sep=0.1, n_informative=40, n_features=50, random_state=0, n_clusters_per_class=10
)
X = pd.DataFrame(X)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5, random_state=42)
# Set up the model:
model = lightgbm.LGBMClassifier(n_estimators=10, num_leaves=7, random_state=0)
import lightgbm
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from sklearn.datasets import make_classification
from sklearn.feature_selection import RFECV
from sklearn.model_selection import cross_val_score, train_test_split
from probatus.feature_elimination import ShapRFECV
# Prepare train and test data:
X, y = make_classification(
n_samples=10000, class_sep=0.1, n_informative=40, n_features=50, random_state=0, n_clusters_per_class=10
)
X = pd.DataFrame(X)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5, random_state=42)
# Set up the model:
model = lightgbm.LGBMClassifier(n_estimators=10, num_leaves=7, random_state=0)
Now, we can run ShapRFECV and RFECV with the same parameters, to extract the optimal feature sets:
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# Run RFECV and ShapRFECV with the same parameters
rfe = RFECV(model, step=1, cv=20, scoring="roc_auc", n_jobs=3).fit(X_train, y_train)
shap_elimination = ShapRFECV(model=model, step=1, cv=20, scoring="roc_auc", n_jobs=3, random_state=0)
shap_report = shap_elimination.fit_compute(X_train, y_train)
# Compare the CV Validation AUC for different number of features in each method.
ax = pd.DataFrame(
{
"RFECV Validation AUC": list(reversed(rfe.cv_results_["mean_test_score"])),
"ShapRFECV Validation AUC": shap_report["val_metric_mean"].values.tolist(),
},
index=shap_report["num_features"].values.tolist(),
).plot(ylim=(0.5, 0.7), rot=10, title="Comparison of RFECV and ShapRFECV", figsize=(10, 5))
ax.set_ylabel("Model Performance")
ax.set_xlabel("Number of features")
ax.invert_xaxis()
plt.show()
# Run RFECV and ShapRFECV with the same parameters
rfe = RFECV(model, step=1, cv=20, scoring="roc_auc", n_jobs=3).fit(X_train, y_train)
shap_elimination = ShapRFECV(model=model, step=1, cv=20, scoring="roc_auc", n_jobs=3, random_state=0)
shap_report = shap_elimination.fit_compute(X_train, y_train)
# Compare the CV Validation AUC for different number of features in each method.
ax = pd.DataFrame(
{
"RFECV Validation AUC": list(reversed(rfe.cv_results_["mean_test_score"])),
"ShapRFECV Validation AUC": shap_report["val_metric_mean"].values.tolist(),
},
index=shap_report["num_features"].values.tolist(),
).plot(ylim=(0.5, 0.7), rot=10, title="Comparison of RFECV and ShapRFECV", figsize=(10, 5))
ax.set_ylabel("Model Performance")
ax.set_xlabel("Number of features")
ax.invert_xaxis()
plt.show()
[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001171 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000838 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001032 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000940 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000915 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000836 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000906 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000902 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000882 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000969 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001013 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000805 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001116 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000886 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000970 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001410 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001604 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001092 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001650 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001176 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001065 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.002925 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000686 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000933 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000740 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001145 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000738 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.002417 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001140 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000786 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001589 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000820 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000719 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001476 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000732 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000826 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001368 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000786 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000758 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001101 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001061 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000744 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000675 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000796 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000741 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000693 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000771 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000663 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000914 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000837 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000762 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000652 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000953 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000638 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001017 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000763 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000928 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000634 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001231 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000919 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000639 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000501 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000811 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000443 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000732 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000767 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000560 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000651 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000584 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000600 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000616 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000547 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001152 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000696 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000742 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000529 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000513 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000655 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000635 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000679 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000615 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000741 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000539 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000759 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001001 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001129 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000825 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001169 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 5355[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000636 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000662 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000502 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000717 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000577 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000471 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000511 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000509 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000666 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000703 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000566 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000565 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000632 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000510 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000572 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000587 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000704 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000584 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000601 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000556 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000575 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000523 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000619 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000380 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000436 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000737 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000545 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000374 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000650 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000486 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000520 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000365 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000373 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000550 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000397 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000302 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000454 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000442 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000279 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000548 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000426 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000500 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000553 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000331 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000455 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000371 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000528 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000432 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000338 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000453 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000443 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000319 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000386 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000359 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000647 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000513 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000150 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000550 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000141 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000383 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000820 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000419 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000149 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000937 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001021 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000895 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001064 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001713 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000833 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001018 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000810 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000896 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000934 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001791 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000929 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000987 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001296 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000709 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000812 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001391 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000871 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000861 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000978 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000753 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001019 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001132 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000773 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000754 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000857 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000823 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000774 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001024 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001015 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000966 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000881 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000866 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000837 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000804 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000861 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000889 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001031 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000770 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001033 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000755 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000710 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000709 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000976 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001023 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000851 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000546 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000951 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000706 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000927 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001165 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000741 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000577 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000730 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000602 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001255 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000964 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001337 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000660 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000705 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000697 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000552 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000681 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000725 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000536 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000767 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000666 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000763 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000520 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000554 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140[LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001279 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000587 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000626 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000576 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000507 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000607 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000409 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000679 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000648 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000632 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000478 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000566 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000526 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000637 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000650 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000599 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000645 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000811 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 5610[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000635 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000472 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000535 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000461 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000557 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000606 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000421 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000675 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000384 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000375 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000404 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000577 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000623 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000695 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000578 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000862 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000556 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000527 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000543 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000589 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000664 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000379 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000354 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000464 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000449 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000439 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000432 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000384 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000406 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000392 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000537 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000533 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000485 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000551 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000400 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000573 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000433 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000236 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000269 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000383 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000509 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000457 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000469 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000494 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000343 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000556 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000312 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000472 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000357 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000514 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000582 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000349 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000360 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000394 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000337 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000396 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000423 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000202 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000245 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000798 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000292 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000911 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000869 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000304 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000811 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001022 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000773 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000855 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001027 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001878 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.002549 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000901 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000971 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000914 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000832 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000983 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000825 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000722 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000983 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001255 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000801 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000893 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000804 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000951 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000907 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001408 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000849 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000876 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000956 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001019 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000918 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000954 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000988 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001226 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000851 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000828 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000762 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000908 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000740 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000768 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000751 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000543 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000968 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000661 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.002441 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000699 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000544 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001430 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000523 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000769 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000646 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000786 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000661 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000620 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000674 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000624 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000787 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000699 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000765 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000725 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000629 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000910 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000717 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000715 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000431 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000687 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000784 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000595 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000603 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000685 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001460 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000536 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000499 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000589 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000984 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000780 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000552 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000678 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000627 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000495 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000617 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000633 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000403 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000413 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000730 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000574 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000540 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000532 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000477 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001072 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000766 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000468 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000617 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000553 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000640 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000687 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000697 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000590 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000353 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000438 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000671 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000355 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000459 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000568 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000542 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000458 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000438 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000394 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000401 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000574 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000419 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000483 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000995 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000410 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000443 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000369 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000428 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000717 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000394 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000426 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000595 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000486 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000550 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000345 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000403 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000595 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000365 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000424 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000450 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000361 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000324 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000556 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000409 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000268 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000467 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000448 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000357 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000423 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000494 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000264 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000430 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000382 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000418 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000472 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000379 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000439 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000346 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000349 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000312 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000976 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000401 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000478 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000778 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000810 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000956 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000854 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000981 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000881 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000920 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001306 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000863 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000855 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.002509 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000995 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000788 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001166 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000770 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000951 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000893 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000892 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000863 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000843 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000710 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000740 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001001 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000916 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000825 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000840 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000690 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000745 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001078 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000804 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001134 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000819 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000818 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000692 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000813 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000798 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000910 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000790 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000701 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000736 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000958 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000832 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000660 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000835 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000713 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000694 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000743 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000801 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000709 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000579 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000714 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000636 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000993 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000490 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000712 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000956 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000610 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000677 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000577 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000723 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000604 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000538 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000734 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000644 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000792 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000501 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000586 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000714 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000579 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000696 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000596 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000656 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000693 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000686 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000513 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000425 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000868 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000706 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000525 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000552 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000690 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000639 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000561 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000514 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000417 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000554 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000499 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000645 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000504 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000549 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000621 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000661 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000421 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000642 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000617 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000480 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000699 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000214 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000478 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000515 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000574 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000572 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000549 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000390 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000572 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000554 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000380 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000669 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000439 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000922 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000459 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000492 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000425 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000448 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000449 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000328 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000312 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000572 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000399 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000340 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000526 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000589 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000674 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000710 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000285 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000316 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000424 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000552 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000452 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000449 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000487 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000492 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530[LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000444 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000392 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000244 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000471 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000347 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000338 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000348 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000177 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000390 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000375 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000380 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000285 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000383 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000321 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000586 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000813 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001162 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000453 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000900 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000421 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001097 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000941 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000895 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000866 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000925 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000950 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000815 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000865 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001350 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001240 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000817 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000890 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000756 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000809 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000788 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000863 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000795 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.002035 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000900 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000971 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001188 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001219 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000804 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001398 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000905 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000777 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000595 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001114 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001046 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000631 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000785 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000887 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000784 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000571 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000795 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000838 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000568 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000666 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000684 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000514 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000715 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000830 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001378 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000789 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000798 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001250 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000958 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000800 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001040 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001056 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Total Bins 7905[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000830 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001342 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000657 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000833 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000574 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000602 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000678 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000660 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000595 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000701 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000950 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000653 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001178 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000671 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000701 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000597 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000517 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000784 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000656 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000748 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000626 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000627 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000724 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000679 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000937 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000762 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000596 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000774 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000789 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000632 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000639 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000485 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000594 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000697 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000592 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000574 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000646 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000555 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000518 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000606 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000694 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000524 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000587 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000515 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000519 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000620 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000563 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000404 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000559 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000627 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000595 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000486 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000767 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000483 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000514 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000511 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000488 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000510 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000468 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000462 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000463 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805[LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000757 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000642 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000802 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000286 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000493 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000468 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000410 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000463 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000802 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000327 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000517 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000643 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000316 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000363 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000359 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000526 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000440 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000498 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000397 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000559 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000305 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000334 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000468 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000387 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000346 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000548 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000197 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000304 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000670 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000245 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000368 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000864 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000338 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000411 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000987 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000347 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000800 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000922 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000446 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000304 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000833 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000956 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000952 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000820 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000954 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000961 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000857 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000757 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000825 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001030 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000924 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001759 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000985 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000959 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 11985[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000794 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000880 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000836 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000844 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000835 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000782 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000686 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000767 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000977 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000917 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000808 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000735 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000886 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000791 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000750 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000635 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000697 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000907 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000793 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001027 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000911 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000766 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.002575 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000761 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000731 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000584 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001577 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000760 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000728 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000749 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000883 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001877 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000961 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000939 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000507 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000739 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000696 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000667 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000813 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000543 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001136 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000622 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000664 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001098 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000638 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000829 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000716 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000957 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000677 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000687 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000807 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000541 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000850 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000857 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000520 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000708 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000518 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000827 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000544 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000505 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000454 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000545 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000554 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000662 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000538 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000606 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000653 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000617 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000626 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000505 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000544 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000641 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000563 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000467 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000564 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000527 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000470 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000632 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000453 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000511 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000566 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000801 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000466 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000615 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000311 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000403 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000690 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000456 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000401 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000564 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000356 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000368 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000553 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000561 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000501 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000463 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000692 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000950 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001715 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000524 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000414 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000636 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000343 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000629 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000580 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000352 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000523 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000435 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000500 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000445 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000481 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000435 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000567 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000501 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000374 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000458 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000388 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000452 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000336 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000321 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000484 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000656 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000585 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000885 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000344 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000373 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000110 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000327 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000880 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000850 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000871 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001362 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000881 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000841 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000850 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000974 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000480 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001340 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000826 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000398 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000252 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684[LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000914 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000822 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000644 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000829 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000653 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000741 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000775 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000762 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000851 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000786 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000752 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000808 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000659 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000736 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000746 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000851 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000596 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000605 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000709 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000670 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000607 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000532 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000624 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000590 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35[LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000662 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000617 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000658 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000563 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000613 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000588 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000644 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000595 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000611 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000571 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000511 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000547 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000467 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000615 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000484 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000582 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000609 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000604 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000520 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000474 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000489 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000548 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000525 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000430 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000542 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000627 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000620 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000546 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000516 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000436 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000443 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000492 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000445 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000554 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000454 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000415 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000552 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000475 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000540 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000862 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000480 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000495 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315[LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000278 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000453 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000298 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000402 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000441 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000413 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000239 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000327 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000390 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000384 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000350 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000405 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000325 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000297 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000294 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000379 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000250 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000301 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000299 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000307 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000266 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000268 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000220 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000279 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000207 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000836 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000775 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000658 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000759 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000754 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000715 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000617 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000636 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000593 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000696 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000546 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000548 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000640 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000580 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000576 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000490 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000531 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000594 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000587 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000507 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000540 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000474 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000453 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000503 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000388 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000452 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000381 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000444 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000477 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000403 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000372 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000424 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000376 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000383 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000385 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000331 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000311 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000896 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001125 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000858 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000943 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000782 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000995 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001858 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.002042 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001591 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001118 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001139 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000932 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000954 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001077 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001122 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001114 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001157 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000990 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001010 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000831 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001035 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001052 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001032 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001778 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000966 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000897 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000921 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000936 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000922 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.002404 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000870 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001091 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001023 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001356 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001079 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000790 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000947 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000917 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.001684[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000736 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000772 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Total Bins 12495 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 49 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001230 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000983 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000995 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000849 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000935 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000951 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001752 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000862 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000822 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000918 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001061 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000824 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000944 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001010 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000768 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001573 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000908 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001012 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000702 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000812 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 12240 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 48 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000806 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000860 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000858 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001020 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000935 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001040 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001105 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001324 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000962 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001142 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000983 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000938 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000793 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001065 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001023 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001080 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001028 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001020 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000785 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000791 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11985 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 47[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001006 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001135 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001095 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.002085 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001180 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001126 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001208 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001242 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001082 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000969 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001000 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000890 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000909 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001213 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000891 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000855 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001452 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000944 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000992 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000932 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11730 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 46 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000937 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000867 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000925 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001075 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001112 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001116 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000711 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000913 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000909 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001003 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000943 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001062 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000818 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000906 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000881 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000873 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000929 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.001684[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000904 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000773 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000753 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 11475 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 45 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000987 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000866 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000981 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000719 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000857 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000795 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001437 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000886 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001070 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000686 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000918 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000954 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000805 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000881 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000814 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001093 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000915 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000874 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000729 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000754 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Total Bins 11220 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 44[LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001088 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001240 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001953 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001081 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000956 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000978 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000987 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001015 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001131 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000926 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001212 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000856 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000740 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000929 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001033 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000815 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000969 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000809 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000840 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000647 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10965 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 43 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000938 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000917 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000983 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000578 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000795 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001003 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000575 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000948 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000801 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000725 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001847 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000771 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001128 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001163 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000927 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001014 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001178 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000770 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000858 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000824 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10710 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 42 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000857 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000905 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000779 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001030 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000844 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000855 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000857 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000793 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000778 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000855 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000945 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000898 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000964 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000814 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000841 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000649 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000837 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000899 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000731 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000625 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10455 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 41 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000570 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000751 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000794 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000523 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000725 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000834 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000720 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000548 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000879 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001080 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001815 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000869 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000934 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000937 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000799 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001029 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000944 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000836 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000722 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000704 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 10200 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 40 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000574 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000810 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000701 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000560 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000800 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000763 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000814 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001155 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000911 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000850 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000823 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000723 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000837 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000868 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000900 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001083 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000844 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000706 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000762 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000764 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] Total Bins 9945 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 39 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000861 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000945 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000909 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000844 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000831 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000850 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001290 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001440 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001340 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000715 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000728 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.002314 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000454 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001034 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001010 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001148 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001238 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001011 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000926 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000630 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9690 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 38 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000973 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000943 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000828 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000754 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000755 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000753 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000798 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000845 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000676 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000921 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000928 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000807 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000749 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000707 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000782 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001737 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000817 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000608 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000677 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000693 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9435 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 37 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001027 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001055 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000903 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000665 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000698 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000689 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000774 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000782 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001002 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001234 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001151 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000634 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001654 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001170 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000878 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000556 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001103 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000623 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000594 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000698 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 9180 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 36 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000857 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000841 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000753 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001094 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000749 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000749 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000760 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000731 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000709 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000848 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000775 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000608 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000737 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000681 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000981 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000736 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000685 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000812 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000444 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000506 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8925 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 35 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000838 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000777 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000840 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000697 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000647 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000718 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 8670[LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000926 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000560 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000627 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001409 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000560 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000629 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001560 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000805 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000817 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001304 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000771 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000918 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000571 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000508 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 8670 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 34 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001459 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000977 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001322 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000675 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000615 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000636 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000539 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000658 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000658 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000768 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000637 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000906 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000660 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000681 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000737 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001097 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000659 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000831 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000532 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000565 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 8415 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 33 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001002 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000941 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000881 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000667 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000596 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000666 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000542 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000811 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000732 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000699 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000500 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000724 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000843 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000681 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000637 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000632 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000928 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000772 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000548 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000491 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] Total Bins 8160 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 32 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000784 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000755 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000664 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000681 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000610 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000778 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000857 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000892 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905[LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000747 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000522 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000735 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000721 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000478 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001196 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000708 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000440 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000442 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000450 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000657 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000515 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7905 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 31 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000926 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000984 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000808 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000498 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000691 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000597 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000679 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000761 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000652 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000688 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000741 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000717 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000701 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000681 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000717 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001025 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000663 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000695 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000512 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000573 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7650 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 30 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001271 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001053 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001129 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000645 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000536 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000646 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000585 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000536 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000568 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000873 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000906 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000648 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000791 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000676 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000724 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000665 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000724 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000695 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000530 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000545 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684[LightGBM] [Info] Total Bins 7395 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 29 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000913 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000945 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000791 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000284 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000743 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000759 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000506 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000871 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000680 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000423 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000859 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000657 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000582 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000620 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000662 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000990 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000667 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000666 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000667 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000580 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Total Bins 7140 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 28 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001012 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000970 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000812 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000422 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000544 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000772 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000509 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000949 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000905 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000458 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000520 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000697 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000772 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001103 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000548 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001458 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000828 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000575 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000492 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000476 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Total Bins 6885 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 27 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000676 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000618 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000848 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000646 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000519 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000700 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001000 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000668 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000501 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000954 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000666 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000685 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000537 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000742 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000538 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001899 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000704 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000718 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000501 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000529 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6630 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 26 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000781 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000598 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000725 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000570 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000561 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000562 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000544 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000496 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000640 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000561 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000564 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000656 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001487 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000789 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000694 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000934 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000578 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000625 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000492 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000551 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6375 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 25 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000870 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000955 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000615 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000597 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000784 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000604 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000653 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000611 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000621 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000610 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000538 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000483 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000612 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000498 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000584 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000716 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000587 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000585 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000601 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000574 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 6120 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 24 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000732 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000685 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000556 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000778 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000710 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000506 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000481 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000485 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000545 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000497 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000483 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000514 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000443 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000522 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001073 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000413 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000519 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000604 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000502 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000541 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Total Bins 5865 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 23 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000878 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000700 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000747 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000934 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000674 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000711 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000485 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000682 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000663 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000481 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000805 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000640 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.001010 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001044 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000623 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000959 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000522 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000656 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000433 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000455 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5610 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 22 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000748 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000638 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000685 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000744 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000520 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000601 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000496 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000481 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000466 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000979 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000661 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000632 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000592 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000622 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000555 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000442 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000599 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000513 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000499 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000551 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] Total Bins 5355 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 21 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000621 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000603 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000671 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000980 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000606 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000483 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000613 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000462 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000412 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000799 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000865 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000613 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000479 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000817 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000432 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000458 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000550 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000538 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000420 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000495 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 5100 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 20 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000701 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000668 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000563 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000510 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000962 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000971 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000444 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000643 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000561 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000442 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000478 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000732 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000431 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000690 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000600 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000566 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000471 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000488 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000376 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000375 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4845 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 19 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000758 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000965 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000712 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000591 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000485 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000451 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000553 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000958 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000572 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000599 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000537 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000586 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000444 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000532 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000577 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000401 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000635 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000485 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000400 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000446 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Total Bins 4590 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 18 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000563 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000605 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000562 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000403 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000512 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000511 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000369 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000415 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000420 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000613 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000440 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000615 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001147 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000620 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000615 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000253 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000426 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000486 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000352 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000493 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4335 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 17 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000477 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000514 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000502 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000417 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000768 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000480 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000340 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000524 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000484 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000353 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000756 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000487 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000429 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000432 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000604 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000367 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000421 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000536 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000347 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000381 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000619 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000632 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000632 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] Total Bins 3825[LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000799 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000887 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000536 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000365 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000332 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000459 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000345 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000362 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000488 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000525 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000436 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000490 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000731 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000639 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000597 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000320 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000423 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000492 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000456 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000489 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000411 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000620 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000474 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000313 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000561 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000544 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000314 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000409 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000547 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000619 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000472 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000466 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000832 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000543 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000480 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000307 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000304 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3570 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 14 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000875 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000656 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000668 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000371 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000511 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000535 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000349 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000388 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000532 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000460 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000388 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000392 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000304 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000404 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000519 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000273 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000465 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000658 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000295 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000433 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3315 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 13 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000485 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000429 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000475 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000495 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000511 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000394 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000533 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000393 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000568 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000372 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000416 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000623 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000301 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000413 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000381 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000472 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000442 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000473 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000446 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000784 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3060 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 12 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000589 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000576 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000585 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000380 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000420 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000509 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000770 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000396 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000429 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001117 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000496 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000546 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000474 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000525 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000390 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000331 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000688 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000578 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000450 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000304 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Total Bins 2805 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 11 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000374 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000456 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000504 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000410 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000399 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000427 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000346 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000371 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000453 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000305 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000321 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000444 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000435 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000509 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000457 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000286 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000461 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000604 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000294 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000333 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2550 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 10 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000498 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000493 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000480 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000316 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000495 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000416 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000357 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000455 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000438 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000422 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000655 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000467 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000558 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000452 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000426 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000302 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000511 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000558 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000314 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000321 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2295 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 9 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000567 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000456 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000460 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526[LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000520 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000421 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000393 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000315 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000379 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000450 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000303 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000585 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000501 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000454 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000523 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000411 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000273 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000455 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000392 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000341 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000307 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 2040 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 8 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000563 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000392 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000421 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000396 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000361 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000394 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000290 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000369 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000466 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000284 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000313 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000360 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001317 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.001641 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000422 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000535 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000296 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000438 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000327 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000359 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1785 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 7 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000480 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000495 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000514 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000447 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000329 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000407 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000329 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000369 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000340 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000315 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000320 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000485 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000265 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000440 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000519 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000282 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000341 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000463 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000394 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000387 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1530 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 6 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000611 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000550 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000698 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000245 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000373 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000345 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000291 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000446 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000393 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000341 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000417 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000342 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000218 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000304 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000474 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000325 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000298 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000351 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000331 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000360 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1275 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 5 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684[LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000454 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000500 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000426 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000262 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000342 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000307 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000388 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000201 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000491 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000280 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000183 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000301 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000706 seconds. You can set `force_row_wise=true` to remove the overhead. And if memory is not enough, you can set `force_col_wise=true`. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000190 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000220 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000352 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000288 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000297 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000223 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000258 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 1020 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 4 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372[LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000570 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000536 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000568 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765[LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000330 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000283 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000359 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000212 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000384 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000364 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000290 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000259 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000415 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000264 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000271 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000408 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000238 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000477 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000482 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000290 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000270 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] Total Bins 765 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684[LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 3 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000774 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000731 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000828 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000395 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000394 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000479 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000295 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000391 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000429 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000289 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000326 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000374 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000459 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000471 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000489 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000404 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000445 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000418 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000296 seconds. You can set `force_col_wise=true` to remove the overhead.[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000299 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 510[LightGBM] [Info] Total Bins 510 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 2 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000385 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000380 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000443 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000170 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000292 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000372 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000291 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000271 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000366 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000313 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000302 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000469 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000397 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000381 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526[LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000346 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000204 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2378, number of negative: 2372 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000329 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500632 -> initscore=0.002526 [LightGBM] [Info] Start training from score 0.002526 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000382 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000233 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684 [LightGBM] [Info] Number of positive: 2377, number of negative: 2373 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000279 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 255 [LightGBM] [Info] Number of data points in the train set: 4750, number of used features: 1 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500421 -> initscore=0.001684 [LightGBM] [Info] Start training from score 0.001684
The plot above presents the averaged CV Validation AUC of model performance for each round of the RFE process in both ShapRFECV and RFECV. The optimal number of features is 16 (based on the highest validation metric mean) for the former, and 15 for the latter.
Now we will compare the performance of the model trained on:
- All 50 available features (baseline),
- 15 features selected by RFECV (final),
- 16 features selected by ShapRFECV (final),
- 15 feature selected by ShapRFECV (baseline).
In [5]:
Copied!
n_features_shap = len(shap_elimination.get_reduced_features_set("best")) # 16
n_features_rfecv = int(rfe.n_features_) # 15
# Calculate the AUC using all features.
test_auc_full = model.fit(X_train, y_train).score(X_test, y_test)
val_auc_full = np.mean(cross_val_score(model, X_train, y_train, cv=10))
# Optimal set for RFECV
rfe_features_set = X_train.columns[rfe.support_]
test_auc_rfe = model.fit(X_train[rfe_features_set], y_train).score(X_test[rfe_features_set], y_test)
val_auc_rfe = rfe.cv_results_["mean_test_score"][n_features_rfecv]
# Optimal set for SHAP
shap_feature_set = X_train.columns[shap_elimination.get_reduced_features_set(n_features_shap)]
test_auc_shap = model.fit(X_train[shap_feature_set], y_train).score(X_test[shap_feature_set], y_test)
val_auc_shap = shap_report[shap_report.num_features == n_features_shap]["val_metric_mean"].values[0]
# Same nr of features as RFECV
shap_feature_set_size_rfe = X_train.columns[shap_elimination.get_reduced_features_set(n_features_rfecv)]
test_auc_shap_size_rfe = model.fit(X_train[shap_feature_set_size_rfe], y_train).score(
X_test[shap_feature_set_size_rfe], y_test
)
val_auc_shap_size_rfe = shap_report[shap_report.num_features == n_features_rfecv]["val_metric_mean"].values[0]
# Plot Test and Validation Performance
variants = (
"All 50 features",
f"RFECV {n_features_rfecv} features",
f"ShapRFECV {n_features_shap} features",
f"ShapRFECV {n_features_rfecv} features",
)
results_test = [test_auc_full, test_auc_rfe, test_auc_shap, test_auc_shap_size_rfe]
results_val = [val_auc_full, val_auc_rfe, val_auc_shap, val_auc_shap_size_rfe]
ax = pd.DataFrame({"CV Validation AUC": results_val, "Test AUC": results_test}, index=variants).plot.bar(
ylim=(0.5, 0.6), rot=10, title="Comparison of RFECV and ShapRFECV", figsize=(10, 5)
)
plt.axhline(y=0.5)
ax.set_ylabel("Model Performance")
plt.show()
n_features_shap = len(shap_elimination.get_reduced_features_set("best")) # 16
n_features_rfecv = int(rfe.n_features_) # 15
# Calculate the AUC using all features.
test_auc_full = model.fit(X_train, y_train).score(X_test, y_test)
val_auc_full = np.mean(cross_val_score(model, X_train, y_train, cv=10))
# Optimal set for RFECV
rfe_features_set = X_train.columns[rfe.support_]
test_auc_rfe = model.fit(X_train[rfe_features_set], y_train).score(X_test[rfe_features_set], y_test)
val_auc_rfe = rfe.cv_results_["mean_test_score"][n_features_rfecv]
# Optimal set for SHAP
shap_feature_set = X_train.columns[shap_elimination.get_reduced_features_set(n_features_shap)]
test_auc_shap = model.fit(X_train[shap_feature_set], y_train).score(X_test[shap_feature_set], y_test)
val_auc_shap = shap_report[shap_report.num_features == n_features_shap]["val_metric_mean"].values[0]
# Same nr of features as RFECV
shap_feature_set_size_rfe = X_train.columns[shap_elimination.get_reduced_features_set(n_features_rfecv)]
test_auc_shap_size_rfe = model.fit(X_train[shap_feature_set_size_rfe], y_train).score(
X_test[shap_feature_set_size_rfe], y_test
)
val_auc_shap_size_rfe = shap_report[shap_report.num_features == n_features_rfecv]["val_metric_mean"].values[0]
# Plot Test and Validation Performance
variants = (
"All 50 features",
f"RFECV {n_features_rfecv} features",
f"ShapRFECV {n_features_shap} features",
f"ShapRFECV {n_features_rfecv} features",
)
results_test = [test_auc_full, test_auc_rfe, test_auc_shap, test_auc_shap_size_rfe]
results_val = [val_auc_full, val_auc_rfe, val_auc_shap, val_auc_shap_size_rfe]
ax = pd.DataFrame({"CV Validation AUC": results_val, "Test AUC": results_test}, index=variants).plot.bar(
ylim=(0.5, 0.6), rot=10, title="Comparison of RFECV and ShapRFECV", figsize=(10, 5)
)
plt.axhline(y=0.5)
ax.set_ylabel("Model Performance")
plt.show()
[LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000759 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2253, number of negative: 2247 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000775 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4500, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500667 -> initscore=0.002667 [LightGBM] [Info] Start training from score 0.002667 [LightGBM] [Info] Number of positive: 2253, number of negative: 2247 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000692 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4500, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500667 -> initscore=0.002667 [LightGBM] [Info] Start training from score 0.002667 [LightGBM] [Info] Number of positive: 2253, number of negative: 2247 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000675 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4500, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500667 -> initscore=0.002667 [LightGBM] [Info] Start training from score 0.002667 [LightGBM] [Info] Number of positive: 2253, number of negative: 2247 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000653 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4500, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500667 -> initscore=0.002667 [LightGBM] [Info] Start training from score 0.002667 [LightGBM] [Info] Number of positive: 2253, number of negative: 2247 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000710 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4500, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500667 -> initscore=0.002667 [LightGBM] [Info] Start training from score 0.002667 [LightGBM] [Info] Number of positive: 2253, number of negative: 2247 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000769 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4500, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500667 -> initscore=0.002667 [LightGBM] [Info] Start training from score 0.002667 [LightGBM] [Info] Number of positive: 2253, number of negative: 2247 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000725 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4500, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500667 -> initscore=0.002667 [LightGBM] [Info] Start training from score 0.002667 [LightGBM] [Info] Number of positive: 2252, number of negative: 2248 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000648 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4500, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500444 -> initscore=0.001778 [LightGBM] [Info] Start training from score 0.001778 [LightGBM] [Info] Number of positive: 2252, number of negative: 2248 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000726 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4500, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500444 -> initscore=0.001778 [LightGBM] [Info] Start training from score 0.001778 [LightGBM] [Info] Number of positive: 2252, number of negative: 2248 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000717 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 12750 [LightGBM] [Info] Number of data points in the train set: 4500, number of used features: 50 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500444 -> initscore=0.001778 [LightGBM] [Info] Start training from score 0.001778 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000357 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000289 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 4080 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 16 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400 [LightGBM] [Info] Number of positive: 2503, number of negative: 2497 [LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000341 seconds. You can set `force_col_wise=true` to remove the overhead. [LightGBM] [Info] Total Bins 3825 [LightGBM] [Info] Number of data points in the train set: 5000, number of used features: 15 [LightGBM] [Info] [binary:BoostFromScore]: pavg=0.500600 -> initscore=0.002400 [LightGBM] [Info] Start training from score 0.002400
As shown in the plot, ShapRFECV provides superior results for both: CV Validation and Test AUC, compared to RFECV and the baseline model with all the available features. Not only the introduced method allows to eliminate features without the loss in performance, but also it may increase the performance of the model.
When it comes to time required to perform the feature selection in the experiment above, RFECV takes 6.11 s ± 33.7 ms, while ShapRFECV takes 10.1 s ± 72.8 ms, which shows that the latter is more computation expensive, due to SHAP values calculation.