pyepo.twostage.sklearnpred
==========================

.. py:module:: pyepo.twostage.sklearnpred

.. autoapi-nested-parse::

   Two-stage model with Scikit-learn predictor



Functions
---------

.. autoapisummary::

   pyepo.twostage.sklearnpred.sklearnPred


Module Contents
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.. py:function:: sklearnPred(pmodel: sklearn.base.BaseEstimator) -> sklearn.multioutput.MultiOutputRegressor

   Wrap a scikit-learn estimator into a multi-output regressor for two-stage baselines.

   The two-stage approach trains a regression model to minimize prediction
   error (e.g. MSE on cost coefficients) and only afterwards plugs the
   predicted costs into the optimization solver. This helper turns any
   single-output scikit-learn estimator (``LinearRegression``,
   ``RandomForestRegressor``, ``MLPRegressor``, ...) into a multi-output
   regressor suitable for predicting the full cost vector.

   :param pmodel: a scikit-learn single-output regression estimator

   :returns: scikit-learn multi-output regression wrapper
   :rtype: MultiOutputRegressor