, l m } = Y is x i 's class label, we want to build a model f (x) that can classify each test instance x to one of the m training or seen classes in Y or reject it to indicate that it does not belong to any of the m training or seen classes, i.e., unseen.
we want to build a (m + 1)-class classifier f (x) with the classes C = {l 1 , l 2 , .