ml_grid.model_classes.H2OGLMClassifier
======================================

.. py:module:: ml_grid.model_classes.H2OGLMClassifier


Classes
-------

.. autoapisummary::

   ml_grid.model_classes.H2OGLMClassifier.H2OGLMClassifier


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

.. py:class:: H2OGLMClassifier(**kwargs)

   Bases: :py:obj:`ml_grid.model_classes.H2OBaseClassifier.H2OBaseClassifier`


   Initializes the H2OGLMClassifier, handling the 'lambda' parameter.

   This wrapper ensures compatibility with scikit-learn's parameter naming
   by accepting `lambda_` and internally mapping it for the H2O backend.

   :param \*\*kwargs: Keyword arguments passed directly to the
                      `H2OGeneralizedLinearEstimator`. Common arguments include
                      `family='binomial'`, `alpha=0.5`, and `lambda_` (for regularization).


   .. py:method:: fit(X: pandas.DataFrame, y: pandas.Series, **kwargs) -> H2OGLMClassifier

      Fits the H2O GLM model and corrects the 'lambda_' parameter name.

      This method first calls the parent `fit` method to train the model.
      After fitting, it ensures the internal H2O model object has the
      regularization parameter named 'lambda' (not 'lambda_') to prevent
      errors during prediction.

      :returns: The fitted classifier instance.
      :rtype: H2OGLMClassifier