GENERALIZATION PERFORMANCE OF MULTI-CATEGORY KERNEL MACHINES——In Memory of Professor Sun Yongsheng

作     者：Hong Chen Luoqing Li 

作者机构：Faculty of Mathematics and Computer Science Hubei University Wuhan 430062 E R. China 

出 版 物：《Analysis in Theory and Applications》 (分析理论与应用（英文刊）)

年 卷 期：2007年第23卷第2期

页      面：188-195页

学科分类：07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：Supported in part by the Specialized Research Fund for the Doctoral Program of Higher Education under grant 20060512001 

主　　题：Kernel machine uniform stability generalization error 

摘      要：Support vector machines are originally designed for binary classification. How to effectively extend it for multi-class classification is still an on-going research issue. In this paper, we consider kernel machines which are natural extensions of multi-category support vector machines originally proposed by Crammer and Singer. Based on the algorithm stability, we obtain the generalization error bounds for the kernel machines proposed in the paper.