Variations on a Kernel-Adatron Theme

The Kernel-Adatron (KA) algorithm was recently introduced as an alternative to quadratic programming for training support vector machines. In this paper we investigate three variants of the original KA algorithm and demonstrate through examples that they deliver excellent accuracy. The examples also show that one of these variants has rather different learning properties to the other two.