Research on noise insensitive SVM based multi-class classifier

被引：0

作者：

Li, K ^{[1
]}

Liu, YS ^{[1
]}

机构：

[1] Beijing Inst Technol, Sch Informat Sci & Technol, Dept Comp Sci & Engn, Beijing 100081, Peoples R China

来源：

PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2004年

关键词：

support vector machine(SVM); noise; multi-class classifier; constraint distance;

D O I：

10.1109/ICMLC.2004.1378593

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A noise insensitive SVM multi-class classifier is proposed. The algorithm is used to analyze data characteristic in the high-dimension data set Firstly a noise insensitive SVM two-class classifier is built to tackle the noise problem. On the basis of standard SVM, constraint distance is also considered to determine the optimal separating hyperplane. According to these, the noise insensitive SVM multi-class classifier is designed with edited SVM, confidence interval and one-against-one method.

引用

页码：3234 / 3237

页数：4

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