The new interpretation of support vector machines on statistical learning theory

The new interpretation of support vector machines

on statistical learning theory

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【期刊名称】《中国科学》 【年(卷),期】2010(000)001

【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. 【总页数】14页(P.151-164) 【

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support;vector;classification;the;minimization;principle;of;the;structural;risk;KKT;conditions 【作者】佚名 【作者单位】;