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.

Example:

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	scikit-learn pipeline instance.	required

Returns:

Name	Type	Description
pipeline	skorecard.pipeline.SkorecardPipeline	modified pipeline instance.

Source code in skorecard/pipeline/pipeline.py

def to_skorecard_pipeline(pipeline: Pipeline) -> SkorecardPipeline:
    """
    Transform a scikit-learn Pipeline to a SkorecardPipeline.

    A SkorecardPipeline is a normal scikit-learn pipeline with some extra methods and attributes.

    Example:

    ```python
    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
    ```

    Args:
        pipeline (Pipeline): `scikit-learn` pipeline instance.

    Returns:
        pipeline (skorecard.pipeline.SkorecardPipeline): modified pipeline instance.
    """
    assert isinstance(pipeline, Pipeline)
    if isinstance(pipeline, SkorecardPipeline):
        return pipeline
    else:
        return SkorecardPipeline(steps=pipeline.steps, memory=pipeline.memory, verbose=pipeline.verbose)

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Last update: 2023-08-08