A Parameters Selection Method of SVM

摘要

An improved artificial fish swarm algorithm called ASFSA is proposed. It could facilitate the selection of values for Step and Visual to meet the balance of algorithm speed and effect. A new SVM parameters selection method based on the ASFSA is described, and the kernel parameter γ and regularization parameter C can both be optimized well. The application case shows that the performance of SVM with optimized parameters is good, so the method is feasible and effective.