Part of Advances in Neural Information Processing Systems 23 (NIPS 2010)
Steinwart was the ﬁrst to prove universal consistency of support vector machine classiﬁcation. His proof analyzed the ‘standard’ support vector machine classiﬁer, which is restricted to binary classiﬁcation problems. In contrast, recent analysis has resulted in the common belief that several extensions of SVM classiﬁcation to more than two classes are inconsistent. Countering this belief, we proof the universal consistency of the multi-class support vector machine by Crammer and Singer. Our proof extends Steinwart’s techniques to the multi-class case.