支持向量机中的模型选择研究

[1] A Study on Sigmoid Kernels for SVM and the Training of Non-PSD Kernels by SMO-type Methods. Lin H T,Lin C J. http://www.chinahtml.com/programming/1/2005/asp-1128242552505.shtml . 2003

[2] 基于RBF核的SVM的模型选择及其应用 [J]. 计算机工程与应用, 2003, (24) : 72 - 73

[3] Choosing Multiple Parameters for Support Vector Machines[J] . Olivier Chapelle,Vladimir Vapnik,Olivier Bousquet,Sayan Mukherjee. &nbspMachine Learning . 2002 (1)

[4] The Nature of Statistical Learning Theory. Vapnik. . 1995

[5] UCI Repository of machine learning data-bases. Newman,D.J.,&Hettich,S.,&Blake,C.L.,&Merz,C.J. http://www.ics.uci.edu/~mlearn/MLReposito-ry.html] . 1998

[6] A practical guide to support vector classification. C.-W.Hsu,,C.-C.Chang,,C.-J.Lin. . 2003

[7] Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel. Keerthi S S,,Lin C J. NeuraI Com-putation . 2003

[1] A Study on Sigmoid Kernels for SVM and the Training of Non-PSD Kernels by SMO-type Methods. Lin H T,Lin C J. http://www.chinahtml.com/programming/1/2005/asp-1128242552505.shtml . 2003

[2] 基于RBF核的SVM的模型选择及其应用 [J]. 计算机工程与应用, 2003, (24) : 72 - 73

[3] Choosing Multiple Parameters for Support Vector Machines[J] . Olivier Chapelle,Vladimir Vapnik,Olivier Bousquet,Sayan Mukherjee. &nbspMachine Learning . 2002 (1)

[4] The Nature of Statistical Learning Theory. Vapnik. . 1995

[5] UCI Repository of machine learning data-bases. Newman,D.J.,&Hettich,S.,&Blake,C.L.,&Merz,C.J. http://www.ics.uci.edu/~mlearn/MLReposito-ry.html] . 1998

[6] A practical guide to support vector classification. C.-W.Hsu,,C.-C.Chang,,C.-J.Lin. . 2003

[7] Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel. Keerthi S S,,Lin C J. NeuraI Com-putation . 2003