:py:mod:`bluecast.preprocessing.target_encoding`
================================================

.. py:module:: bluecast.preprocessing.target_encoding


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   bluecast.preprocessing.target_encoding.BinaryClassTargetEncoder
   bluecast.preprocessing.target_encoding.MultiClassTargetEncoder
   bluecast.preprocessing.target_encoding.RegressionTargetEncoder




.. py:class:: BinaryClassTargetEncoder(cat_columns: List[Union[str, float, int]], random_state: int = 200)


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

   .. py:method:: fit_target_encode_binary_class(x: pandas.DataFrame, y: pandas.Series) -> pandas.DataFrame

      Fit target encoder using NestedCVWrapper and transform columns.


   .. py:method:: transform_target_encode_binary_class(x: pandas.DataFrame) -> pandas.DataFrame

      Transform categories based on already trained encoder.



.. py:class:: MultiClassTargetEncoder(cat_columns: List[Union[str, float, int]], target_col: Union[str, float, int], random_state: int = 200)


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

   .. py:method:: fit_target_encode_multiclass(x: pandas.DataFrame, y: pandas.Series) -> pandas.DataFrame

      Fit target encoder using NestedCVWrapper and transform columns.


   .. py:method:: transform_target_encode_multiclass(x: pandas.DataFrame) -> pandas.DataFrame

      Transform categories based on already trained encoder.



.. py:class:: RegressionTargetEncoder(cat_columns: List[Union[str, float, int]], random_state: int = 200)


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

   .. py:method:: fit_target_encode_regression(x: pandas.DataFrame, y: pandas.Series) -> pandas.DataFrame

      Fit target encoder using NestedCVWrapper and transform columns.


   .. py:method:: transform_target_encode_regression(x: pandas.DataFrame) -> pandas.DataFrame

      Transform categories based on already trained encoder.