An Improvement of Support Vector Machine Parameter Optimization Method
LV Jinrui
Abstract：The penalty parameter and the kernel parameter are the main factors to determine SVMs' generalization performance and the optimization of these two parameters is one of the key issues,which needs to be solved in the application of SVM.Based on the research of SVM theory,through programming,the paper uses some standard test data sets to compare the performance of uniform design method in the RBF kernel SVM parameter optimization problems.Through the comparison of accuracy,it is showed that the further precision can be obtained compared with the traditional method.
Keywords：SVMuniform designRBF kerne
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 1318-1322 )