DirectSVM: a fast and simple support vector machine perceptron
Danny Roobaert · 2002
We propose a simple implementation of the support vector machine (SVM) for pattern recognition, that is not based on solving a complex quadratic optimization problem. Instead we propose a simple, iterative algorithm that is based on a few simple heuristics. The proposed algorithm finds high-quality solutions in a fast and intuitively-simple way. In experiments on the COIL database, on the extended COIL database and on the Sonar database of the UCI Irvine repository, DirectSVM is able to find solutions that are similar to these found by the original SVM. However DirectSVM is able to find these solutions substantially faster, while requiring less computational resources than the original SVM.