The `KFold.split` function in the Python scikit-learn library (sklearn) is used for creating a generator that splits a dataset into training and test sets for cross-validation. It takes the number of samples in the dataset and the desired number of folds as input parameters. The function returns a generator that yields indices to split the dataset into training and test sets. Each fold iteration yields two arrays of indices, one for the training set and the other for the test set. This function is commonly used for evaluating the performance and generalization of machine learning models.
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