bluecast.preprocessing.target_encoding

Module Contents

Classes

BinaryClassTargetEncoder	Target encode categorical features in the context of binary classification using NestedCVWrapper.
MultiClassTargetEncoder	Target encode categorical features in the context of multiclass classification using NestedCVWrapper.
RegressionTargetEncoder	Target encode categorical features in the context of regression using NestedCVWrapper.

class bluecast.preprocessing.target_encoding.BinaryClassTargetEncoder(cat_columns: List[str | float | int], random_state: int = 200)

Target encode categorical features in the context of binary classification using NestedCVWrapper.

fit_target_encode_binary_class(x: pandas.DataFrame, y: pandas.Series) → pandas.DataFrame

Fit target encoder using NestedCVWrapper and transform columns.

transform_target_encode_binary_class(x: pandas.DataFrame) → pandas.DataFrame

Transform categories based on already trained encoder.

class bluecast.preprocessing.target_encoding.MultiClassTargetEncoder(cat_columns: List[str | float | int], target_col: str | float | int, random_state: int = 200)

Target encode categorical features in the context of multiclass classification using NestedCVWrapper.

fit_target_encode_multiclass(x: pandas.DataFrame, y: pandas.Series) → pandas.DataFrame

Fit target encoder using NestedCVWrapper and transform columns.

transform_target_encode_multiclass(x: pandas.DataFrame) → pandas.DataFrame

Transform categories based on already trained encoder.

class bluecast.preprocessing.target_encoding.RegressionTargetEncoder(cat_columns: List[str | float | int], random_state: int = 200)

Target encode categorical features in the context of regression using NestedCVWrapper.

fit_target_encode_regression(x: pandas.DataFrame, y: pandas.Series) → pandas.DataFrame

Fit target encoder using NestedCVWrapper and transform columns.

transform_target_encode_regression(x: pandas.DataFrame) → pandas.DataFrame

Transform categories based on already trained encoder.