bigframes.ml.model_selection.KFold.split

KFold.split(X: DataFrame | Series | DataFrame | Series, y: DataFrame | Series | DataFrame | Series | None = None) → Generator[tuple[DataFrame | Series | None, ...], None, None]

Generate indices to split data into training and test set.

Parameters:

• X (bigframes.dataframe.DataFrame or bigframes.series.Series) – BigFrames DataFrame or Series of shape (n_samples, n_features) Training data, where n_samples is the number of samples and n_features is the number of features.

• y (bigframes.dataframe.DataFrame, bigframes.series.Series or None) – BigFrames DataFrame, Series of shape (n_samples,) or None. The target variable for supervised learning problems. Default to None.

Yields:

X_train (bigframes.dataframe.DataFrame or bigframes.series.Series) – The training data for that split.

X_test (bigframes.dataframe.DataFrame or bigframes.series.Series):

The testing data for that split.

y_train (bigframes.dataframe.DataFrame, bigframes.series.Series or None):

The training label for that split.

y_test (bigframes.dataframe.DataFrame, bigframes.series.Series or None):

The testing label for that split.