Class-Specific Feature Selection for One-Against-All Multiclass SVMs

This paper proposes a method to perform class-specic fea- ture selection in multiclass support vector machines addressed with the one-against-all strategy. The main issue arises at the nal step of the classication process, where binary classier outputs must be compared one against another to elect the winning class. This comparison may be biased towards one specic class when the binary classiers are built on distinct feature subsets. This paper proposes a normalization of the binary classiers outputs that allows fair comparisons in such cases.