A support vector machine with integer parameters

Abstract

We describe here a method for building a support vector machine (SVM) with integer parameters. Our method is based on a branch-and-bound procedure, derived from modern mixed integer quadratic programming solvers, and is useful for implementing the feed-forward phase of the SVM in fixed–point arithmetic. This allows the implementation of the SVM algorithm on resource–limited hardware like, for example, computing devices used for building sensor networks, where floating–point units are rarely available. The experimental results on well–known benchmarking data sets and a real–world people-detection application show the effectiveness of our approach.