bigframes.ml.ensemble.RandomForestRegressor.fit#

RandomForestRegressor.fit(X:DataFrame|Series|DataFrame|Series,y:DataFrame|Series|DataFrame|Series,X_eval:DataFrame|Series|DataFrame|Series|None=None,y_eval:DataFrame|Series|DataFrame|Series|None=None)→_T#

Build a forest of trees from the training set (X, y).

Parameters:

• X (bigframes.dataframe.DataFrame orbigframes.series.Series orpandas.core.frame.DataFrame orpandas.core.series.Series) – Series or DataFrame of shape (n_samples, n_features). Training data.

• y (bigframes.dataframe.DataFrame orbigframes.series.Series orpandas.core.frame.DataFrame orpandas.core.series.Series) – Series or DataFrame of shape (n_samples,) or (n_samples, n_targets).Target values. Will be cast to X’s dtype if necessary.

• X_eval (bigframes.dataframe.DataFrame orbigframes.series.Series orpandas.core.frame.DataFrame orpandas.core.series.Series) – Series or DataFrame of shape (n_samples, n_features). Evaluation data.

• y_eval (bigframes.dataframe.DataFrame orbigframes.series.Series orpandas.core.frame.DataFrame orpandas.core.series.Series) – Series or DataFrame of shape (n_samples,) or (n_samples, n_targets).Evaluation target values. Will be cast to X_eval’s dtype if necessary.

Returns:

Fitted estimator.

Return type:

ForestModel