To skorecard pipeline
Transform a scikit-learn Pipeline to a SkorecardPipeline.
A SkorecardPipeline is a normal scikit-learn pipeline with some extra methods and attributes.
Examples:
from skorecard.pipeline.pipeline import SkorecardPipeline, to_skorecard_pipeline
from skorecard.bucketers import DecisionTreeBucketer, OrdinalCategoricalBucketer
from skorecard import datasets
from sklearn.pipeline import make_pipeline
pipe = make_pipeline(
DecisionTreeBucketer(variables = ["LIMIT_BAL", "BILL_AMT1"],max_n_bins=5),
OrdinalCategoricalBucketer(variables = ["EDUCATION", "MARRIAGE"], tol =0.05)
)
sk_pipe = to_skorecard_pipeline(pipe)
df = datasets.load_uci_credit_card(as_frame=True)
features = ["LIMIT_BAL", "BILL_AMT1", "EDUCATION", "MARRIAGE"]
X = df[features]
y = df["default"].values
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
pipeline |
Pipeline |
|
required |
Returns:
| Type | Description |
|---|---|
pipeline (skorecard.pipeline.SkorecardPipeline) |
modified pipeline instance. |
Last update: 2021-11-24