Speeding up SVM decision based on mirror points

Abstract

In this paper, we propose a new method to speed up SVM decision based on the idea of mirror points. Decisions based on multiple simple classifiers, which are formed as a result of mirror pairs, are combined to approximate a single SVM. A dynamic programming-based method is used to find a suitable combination. Experimental results show that this method can increase classification efficiencies of SVM with comparable classification performances.