Parameters Optimization of SVM Based on Genetic Algorithm
CAO Lu
OUYANG Xiaoyuan
Abstract：The performance of SVM is mainly affected by the kernel function parameters and penalty parameter .SVM with RBF kernel function is the most widely applications .Using genetic algorithm to select optimum parameter ,the paper mainly studies the performance of SVM with penalty parameter C and RBF kernel function parameter σ .Comparing grid search with genetic algorithm for optimum parameter to SVM based on RBF kernel function in experimental results ,it is found that genetic algorithm has higher search speed in optimum parameter .Thus ,genetic algorithm is more effective in practice .
Keywords：SVMkernel functionparametergenetic algorithm
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 575-577,595 )