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ERROR ANALYSIS OF MULTICATEGORY SUPPORT VECTOR MACHINE CLASSIFIERS

ERROR ANALYSIS OF MULTICATEGORY SUPPORT VECTOR MACHINE CLASSIFIERS
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摘要 The paper is related to the error analysis of Multicategory Support Vector Machine （MSVM） classifiers based on reproducing kernel Hilbert spaces. We choose the polynomial kernel as Mercer kernel and give the error estimate with De La Vall6e Poussin means. We also introduce the standard estimation of sample error, and derive the explicit learning rate. The paper is related to the error analysis of Multicategory Support Vector Machine （MSVM） classifiers based on reproducing kernel Hilbert spaces. We choose the polynomial kernel as Mercer kernel and give the error estimate with De La Vall6e Poussin means. We also introduce the standard estimation of sample error, and derive the explicit learning rate.
作者 Lei Ding BaohuaiSheng
机构地区 Ningbo University Shaoxing University
出处 《Analysis in Theory and Applications》 2010年第2期153-173,共21页 分析理论与应用（英文刊）
基金 Supported by the National NSF(10871226) of PRC
关键词 support vector machine classification learning rate reproducing kernel Hilbert spaces De La Vall^e Poussin means support vector machine classification, learning rate, reproducing kernel Hilbert spaces, De La Vall^e Poussin means
分类号 O211.9 [理学—概率论与数理统计] TP311.13 [自动化与计算机技术—计算机软件与理论]
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共引文献5

Analysis in Theory and Applications
2010年 第2期

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