museotoolbox.cross_validation.RandomStratifiedKFold.split

RandomStratifiedKFold.split(X, y, groups=None)

Split the vector/array according to y and groups.

Parameters

• X (array-like, shape (n_samples, n_features), optional) – Training data, where n_samples is the number of samples and n_features is the number of features.

• y (array-like, of length n_samples) – The target variable for supervised learning problems.

• groups (array-like, with shape (n_samples,), optional) – Subgroup labels for the samples used while splitting the dataset into train/test set.

Returns

• train (ndarray) – The training set indices for that split.

• test (ndarray) – The testing set indices for that split.