中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
The new interpretation of support vector machines on statistical learning theory

文献类型:期刊论文

作者Zhang ChunHua2; Tian YingJie3; Deng NaiYang1
刊名Science china-mathematics
出版日期2010
卷号53期号:1页码:151-164
关键词C-support vector classification The minimization principle of the structural risk Kkt conditions
ISSN号1674-7283
DOI10.1007/s11425-010-0018-6
通讯作者Deng naiyang(dengnaiyang@vip.163.com)
英文摘要This paper is concerned with the theoretical foundation of support vector machines (svms). the purpose is to develop further an exact relationship between svms and the statistical learning theory (slt). as a representative, the standard c-support vector classification (c-svc) is considered here. more precisely, we show that the decision function obtained by c-svc is just one of the decision functions obtained by solving the optimization problem derived directly from the structural risk minimization principle. in addition, an interesting meaning of the parameter c in c-svc is given by showing that c corresponds to the size of the decision function candidate set in the structural risk minimization principle.
WOS关键词CLASSIFICATION ; CONSISTENCY
WOS研究方向Mathematics
WOS类目Mathematics, Applied ; Mathematics
语种英语
WOS记录号WOS:000276546200013
出版者SCIENCE CHINA PRESS
URI标识http://www.irgrid.ac.cn/handle/1471x/2411799
专题中国科学院大学
通讯作者Deng NaiYang
作者单位1.China Agr Univ, Coll Sci, Beijing 100083, Peoples R China
2.Renmin Univ China, Sch Informat, Beijing 100872, Peoples R China
3.Chinese Acad Sci, Res Ctr Fictitious Econ & Data Sci, Beijing 100080, Peoples R China
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Zhang ChunHua,Tian YingJie,Deng NaiYang. The new interpretation of support vector machines on statistical learning theory[J]. Science china-mathematics,2010,53(1):151-164.
APA Zhang ChunHua,Tian YingJie,&Deng NaiYang.(2010).The new interpretation of support vector machines on statistical learning theory.Science china-mathematics,53(1),151-164.
MLA Zhang ChunHua,et al."The new interpretation of support vector machines on statistical learning theory".Science china-mathematics 53.1(2010):151-164.

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来源:中国科学院大学

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