Automatic parameters selection for SVM based on GA

Motivated by the fact that automatic parameter selection for support vector machines (SVM) is an important issue in order to make the SVM practically useful against the commonly used leave-one-out (loo) method, which has complex calculation and time consuming. An effective strategy for automatic parameter selection for SVM is proposed by using the genetic algorithm (GA) in this paper. Simulation results of the practice data model demonstrate the effectiveness and high efficiency of the proposed approach.