h2o-py/h2o/estimators/estimator_base.py
def train(self, x=None, y=None, training_frame=None, offset_column=None, fold_column=None,
              weights_column=None, validation_frame=None, max_runtime_secs=None, ignored_columns=None,
              model_id=None, verbose=False):
        """
        Train the H2O model.

        :param x: A list of column names or indices indicating the predictor columns.
        :param y: An index or a column name indicating the response column.
        :param H2OFrame training_frame: The H2OFrame having the columns indicated by x and y (as well as any
            additional columns specified by fold, offset, and weights).
        :param offset_column: The name or index of the column in training_frame that holds the offsets.
        :param fold_column: The name or index of the column in training_frame that holds the per-row fold
            assignments.
        :param weights_column: The name or index of the column in training_frame that holds the per-row weights.
        :param validation_frame: H2OFrame with validation data to be scored on while training.
        :param float max_runtime_secs: Maximum allowed runtime in seconds for model training. Use 0 to disable.
        :param bool verbose: Print scoring history to stdout. Defaults to False.
        """
        self._train(x=x, y=y, training_frame=training_frame, offset_column=offset_column, fold_column=fold_column,
                    weights_column=weights_column, validation_frame=validation_frame, max_runtime_secs=max_runtime_secs, 
                    ignored_columns=ignored_columns, model_id=model_id, verbose=verbose)
def train(self, x=None, y=None, training_frame=None, offset_column=None, fold_column=None,
              weights_column=None, validation_frame=None, max_runtime_secs=None, ignored_columns=None,
              model_id=None, verbose=False):
        self._train(x=x, y=y, training_frame=training_frame, offset_column=offset_column, fold_column=fold_column,
                    weights_column=weights_column, validation_frame=validation_frame, max_runtime_secs=max_runtime_secs, 
                    ignored_columns=ignored_columns, model_id=model_id, verbose=verbose)
def train ( self , x = None , y = None , training_frame = None , offset_column = None , fold_column = None , weights_column = None , validation_frame = None , max_runtime_secs = None , ignored_columns = None , model_id = None , verbose = False ) : self . _train ( x = x , y = y , training_frame = training_frame , offset_column = offset_column , fold_column = fold_column , weights_column = weights_column , validation_frame = validation_frame , max_runtime_secs = max_runtime_secs , ignored_columns = ignored_columns , model_id = model_id , verbose = verbose )
Train the H2O model.

        :param x: A list of column names or indices indicating the predictor columns.
        :param y: An index or a column name indicating the response column.
        :param H2OFrame training_frame: The H2OFrame having the columns indicated by x and y (as well as any
            additional columns specified by fold, offset, and weights).
        :param offset_column: The name or index of the column in training_frame that holds the offsets.
        :param fold_column: The name or index of the column in training_frame that holds the per-row fold
            assignments.
        :param weights_column: The name or index of the column in training_frame that holds the per-row weights.
        :param validation_frame: H2OFrame with validation data to be scored on while training.
        :param float max_runtime_secs: Maximum allowed runtime in seconds for model training. Use 0 to disable.
        :param bool verbose: Print scoring history to stdout. Defaults to False.
Train the H2O model .