How to recycle your SVM code to do feature selection

Andre Elisseeff and Jason Weston
BIOwulf Technologies

We present an easy-to-use method to do feature selection that uses Support Vector Machine techniques. The method consists in a minimization of the number of non-zero components of a linear model that has a low empirical error on the training set. It can be applied to two-class problems but also to multi-class, multi-label and regression ones. We will try to motivate the method and will describe the experiments which show that it is at leat as good as many existing feature selection procedures.