Sklearn StratifiedKFold: ValueError: Supported target types are: (‘binary’, ‘multiclass’). Got ‘multilabel-indicator’ instead

keras.utils.to_categorical produces a one-hot encoded class vector, i.e. the multilabel-indicator mentioned in the error message. StratifiedKFold is not designed to work with such input; from the split method docs:

split(X, y, groups=None)

[…]

y : array-like, shape (n_samples,)

The target variable for supervised learning problems. Stratification is done based on the y labels.

i.e. your y must be a 1-D array of your class labels.

Essentially, what you have to do is simply to invert the order of the operations: split first (using your intial y_train), and convert to_categorical afterwards.

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