Ensemble kernel method:SVM classification based on game theory

查看全文 作　　者：Yufei [1,2]Liu;Dechang [1,3]Pi;Qiyou [4]Cheng

机构地区：[1]College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;[2]Department of Computer Science and Technology, Tangshan College, Tangshan 063000, China;[3]Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing 211106, China;[4]China Helicopter Research and Development Institute, Jingdezhen 333001, China

出　　处：《Journal of Systems Engineering and Electronics》索引2016年第27卷第1期,共9页

基　　金：supported by the National Natural Science Foundation of China(U1433116);the Aviation Science Foundation of China(20145752033);the Graduate Innovation Project of Jiangsu Province(KYLX15_0324) 摘　　要：With the development of the support vector machine(SVM),the kernel function has become one of the cores of the research on SVM.To a large extent,the kernel function determines the generalization ability of the classifier,but there is still no general theory to guide the choice and structure of the kernel function.An ensemble kernel function model based on the game theory is proposed,which is used for the SVM classification algorithm.The model can effectively integrate the advantages of the local kernel and the global kernel to get a better classification result,and can provide a feasible way for structuring the kernel function.By making experiments on some standard datasets,it is verified that the new method can significantly improve the accuracy of classification. 关键词：支持向量机分类博弈论成核泛化能力函数模型核函数分类器数据集

相关文献

参考文献（15）
引证文献（6）
耦合文献（6）

参考文献(15)

引证文献(6)

耦合文献(6)

互联网出版许可证新出网证(渝)字10号全国400电话 - 免长途话费

Ensemble kernel method:SVM classification based on game theory

参考文献(15)

引证文献(6)

耦合文献(6)

用户提示