libuplift.meta.base
===================

.. py:module:: libuplift.meta.base

.. autoapi-nested-parse::

   Base classe for uplift meta models.

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Classes
-------

.. autoapisummary::

   libuplift.meta.base.UpliftMetaModelBase


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

.. py:class:: UpliftMetaModelBase(base_estimator)

   Bases: :py:obj:`sklearn.utils.metaestimators._BaseComposition`


   
   Base class for uplift meta estimators.

   Checks input consistency, builds classifiers on subsets of data.

   Derived classess need to overwride the _get_model_names_list and
   _iter_training_subsets methods.  The predict method needs to be
   implemented as well.















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   .. py:method:: fit(X, y, trt, n_trt=None, sample_weight=None, **kwargs)


   .. py:method:: get_params(deep=True)

      
      Get parameters for this estimator.


      :Parameters:

          **deep** : boolean, optional
              If True, will return the parameters for this estimator and
              contained subobjects that are estimators.



      :Returns:

          **params** : mapping of string to any
              Parameter names mapped to their values.











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   .. py:method:: set_params(**kwargs)

      
      Set the parameters of this estimator.

      Valid parameter keys can be listed with ``get_params()``.




      :Returns:

          self
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