ml_grid.model_classes.H2OAutoMLClassifier
=========================================

.. py:module:: ml_grid.model_classes.H2OAutoMLClassifier


Classes
-------

.. autoapisummary::

   ml_grid.model_classes.H2OAutoMLClassifier.H2OAutoMLClassifier


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

.. py:class:: H2OAutoMLClassifier(max_runtime_secs: int = 360, nfolds: int = 2, seed: int = 1)

   Bases: :py:obj:`sklearn.base.BaseEstimator`, :py:obj:`sklearn.base.ClassifierMixin`


   Initializes the H2OAutoMLClassifier.

   :param max_runtime_secs: Maximum time in seconds to run the AutoML process.
   :type max_runtime_secs: int
   :param nfolds: Number of folds for cross-validation.
   :type nfolds: int
   :param seed: Random seed for reproducibility.
   :type seed: int


   .. py:attribute:: max_runtime_secs
      :value: 360



   .. py:attribute:: nfolds
      :value: 2



   .. py:attribute:: seed
      :value: 1



   .. py:attribute:: automl
      :type:  Optional[h2o.automl.H2OAutoML]
      :value: None



   .. py:attribute:: classes_
      :type:  Optional[numpy.ndarray]
      :value: None



   .. py:method:: fit(X: pandas.DataFrame, y: pandas.Series) -> H2OAutoMLClassifier

      Fits the H2O AutoML model.

      This method initializes an H2O cluster, converts the pandas DataFrame
      and Series to H2O Frames, and then trains the AutoML model.

      :param X: The training input samples.
      :type X: pd.DataFrame
      :param y: The target values.
      :type y: pd.Series

      :returns: The fitted estimator.
      :rtype: H2OAutoMLClassifier



   .. py:method:: predict(X: pandas.DataFrame) -> numpy.ndarray

      Predicts class labels for samples in X.

      :param X: The input samples to predict.
      :type X: pd.DataFrame

      :returns: The predicted class labels.
      :rtype: np.ndarray



   .. py:method:: predict_proba(X: pandas.DataFrame) -> numpy.ndarray
      :abstractmethod:


      Predicts class probabilities for samples in X.

      .. note:: This method is not implemented for H2O AutoML.

      :param X: The input samples.
      :type X: pd.DataFrame

      :raises NotImplementedError: H2O AutoML does not support predict_proba.



   .. py:method:: get_params(deep: bool = True) -> Dict[str, Any]

      Gets parameters for this estimator.

      :param deep: If True, will return the parameters for this estimator and
                   contained subobjects that are estimators.
      :type deep: bool

      :returns: Parameter names mapped to their values.
      :rtype: Dict[str, Any]



   .. py:method:: set_params(**params: Any) -> H2OAutoMLClassifier

      Sets the parameters of this estimator.

      :param \*\*params: Estimator parameters.
      :type \*\*params: Any

      :returns: The instance with updated parameters.
      :rtype: H2OAutoMLClassifier



   .. py:method:: get_leader_params() -> Dict[str, Any]

      Gets the parameters of the best model found by AutoML.

      :returns: A dictionary of the leader model's parameters.
      :rtype: Dict[str, Any]