| GENERALIZATION PERFORMANCE OF MULTI-CATEGORY KERNEL MACHINES -In Memory of Professor Sun Yongsheng |
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| 引用本文： | Hong Chen Luoqing Li. GENERALIZATION PERFORMANCE OF MULTI-CATEGORY KERNEL MACHINES -In Memory of Professor Sun Yongsheng[J]. 分析论及其应用, 2007, 23(2): 188-195. DOI: 10.1007/s10496-007-0188-4 |
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| 作者姓名： | Hong Chen Luoqing Li |
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| 作者单位： | Faculty of Mathematics and Computer Science Hubei University Wuhan 430062, E R. China |
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| 基金项目： | 高等学校博士学科点专项科研项目 |
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| 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.
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| 关 键 词： | 支持向量机 核心机器 稳定性 广义性误差 |
| 修稿时间： | 2006-09-282007-02-06 |
Generalization performance of multi-category kernel machines |
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| Hong Chen,Luoqing Li. Generalization performance of multi-category kernel machines[J]. Analysis in Theory and Applications, 2007, 23(2): 188-195. DOI: 10.1007/s10496-007-0188-4 |
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| Authors: | Hong Chen Luoqing Li |
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| Affiliation: | 1.Faculty of Mathematics and Computer Science,Hubei University,Wuhan,P. R. China |
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| Abstract: | 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. |
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| Keywords: | Kernel machine uniform stability generalization error KERNEL PERFORMANCE GENERALIZATION generalization error bounds Based algorithm stability kernel natural extensions support vector machines paper extend research Support binary classification |
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