Version 1.0 breaks cross-validation with string targets about scikit-learn

[stefan6419846]

As some additional data point: Research showed that

scikit-learn/sklearn/calibration.py

Line 392 in 5dbf795

[np.sum(y == class_) < n_folds for class_ in self.classes_]

is the culprit as the array filtering does not seem to work with string-based lists anymore. This seems to indicate that scikit-learn would previously do some conversions for string targets beforehand which were dropped, as git blame does not show a change for this line.

A workaround is to convert my lists to a NumPy array with numpy.asarray() beforehand, but I still think that this is some breaking change/side-effect as integer-based lists continue to work as expected.

[jeremiedbb]

Thanks for the report @stefan6419846. We indeed used to convert y into a ndarray but this conversion is now delegated to the inner estimator.

This method for computing the number of occurrences for each class works if both are numpy arrays but fails when 1 is a list and elements are strings. I opened #28843 to fix it