libuplift.classifiers.classifier_as_regressor
=============================================

.. py:module:: libuplift.classifiers.classifier_as_regressor

.. autoapi-nested-parse::

   Use a classifier as a regressor.

   By default return predicted probabilities as numeric predictions.

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Classes
-------

.. autoapisummary::

   libuplift.classifiers.classifier_as_regressor.ClassifierAsRegressor


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

.. py:class:: ClassifierAsRegressor(estimator, response_method='predict_proba', pos_label=1)

   Bases: :py:obj:`sklearn.base.MetaEstimatorMixin`, :py:obj:`sklearn.base.RegressorMixin`, :py:obj:`sklearn.base.BaseEstimator`


   
   Wraps a classifier such that it behaves like a regressor.

   The predict method returns by default predicted probability for
   class specified by ``pos_label`` (default 1).  The method used for
   prediction can be changed by passing the response_method
   argument.

   If ``response_method returns a vector`` (e.g. ``decision_function``)
   ``pos_label`` will be ignored.

   :Parameters:

       **estimator** : a scikit-klearn classifier
           Classifier to wrap in a regessor interface.

       **response_method** : string, default='predict_proba'
           Classifier's method to use for making predictions.

       **pos_label** : integer, default=1
           Label whose probability should be returned by regressor's
           predict method.














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   .. py:method:: fit(*args, **kwargs)


   .. py:method:: predict(*args, **kwargs)