ptocca
commented
1 year ago Hello, thanks for your question! Venn-ABERS predictors are specifically for binary classification and my package therefore supports only that type of classification. I have not thought long enough to give a proper answer for the multiclass case, but I guess that a possible approach might be to set up C classification problems (where by C I denote the number of classes) of the type one-class-vs-the-rest. You could run the calibration on each of the C classification scores separately and get calibrated probabilities for each label. However I do not think there would be theoretical guarantees that the sum of the probabilities for the C labels of an object would always be exactly 1.
Hello, is this package able to calibrate probabilities for multiclass classification? If not do you know how this can be achieved? Thank you very much in advance for your great package