计算机与数字工程2017，Vol.45Issue(7)：1318-1322,5.DOI:10.3969/j.issn.1672-9722.2017.07.017
一种改进的支持向量机参数寻优方法
An Improvement of Support Vector Machine Parameter Optimization Method
摘要
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.关键词
SVM/均方设计/RBF核参数Key words
SVM/uniform design/RBF kerne分类
信息技术与安全科学引用本文复制引用
吕金锐..一种改进的支持向量机参数寻优方法[J].计算机与数字工程,2017,45(7):1318-1322,5.
