StratifiedKFold与KFold

一、KFold

K-Folds cross-validator Provides train/test indices to split data in train/test sets. Split dataset into k consecutive folds (without shuffling by default). Each fold is then used once as a validation while the k - 1 remaining folds form the training set.

sklearn.model_selection.StratifiedKFold(n_splits=3, shuffle=False, random_state=None)

Methods

• get_n_splits([X, y, groups]): Returns the number of splitting iterations in the cross-validator
• split(X[, y, groups]): Generate indices to split data into training and test set.

StratifiedKFold

Stratified K-Folds cross-validator Provides train/test indices to split data in train/test sets. This cross-validation object is a variation of KFold that returns stratified folds. The folds are made by preserving the percentage of samples for each class.

sklearn.model_selection.StratifiedKFold(n_splits=3, shuffle=False, random_state=None)

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Methods

• get_n_splits([X, y, groups]): Returns the number of splitting iterations in the cross-validator
• split(X, y[, groups]): Generate indices to split data into training and test set.