A method of parameters selection with higher accuracy for SVM

摘要

Based the analysis of the effect of kernel parameters and penalty parameters on the performance of support vector machine(SVM), the paper has proposed a new method of hydroid simulated annealing technology. The experiment run on the datasets of UCI with the algorithm has shown the result with higher accuracy.