:py:mod:`bluecast.blueprints.preprocessing_recipes`
===================================================

.. py:module:: bluecast.blueprints.preprocessing_recipes


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

Classes
~~~~~~~

.. autoapisummary::

   bluecast.blueprints.preprocessing_recipes.PreprocessingForLinearModels




.. py:class:: PreprocessingForLinearModels(num_columns: Optional[List])


   Bases: :py:obj:`bluecast.preprocessing.custom.CustomPreprocessing`

   This class is an entry point for last mile computations before model training or tuning. It is an abstract class
   and must be extended by the user. For fit_transform x_train and y_train are passed. For transform x_test and y_test
   are passed in the BlueCast pipeline. Use prediction_mode = False to skip processing the missing targets.
   :param trained_patterns: Optional. Can we used to save anything from training to be loaded and used in transform.
   If more placeholders are needed, use a dictionary.

   .. py:method:: fit_transform(df: pandas.DataFrame, target: pandas.Series) -> Tuple[pandas.DataFrame, pandas.Series]


   .. py:method:: transform(df: pandas.DataFrame, target: Optional[pandas.Series] = None, predicton_mode: bool = False) -> Tuple[pandas.DataFrame, Optional[pandas.Series]]

      Use prediction mode to not process the missing target during inference.