Fuzzy support vector classification based on fuzzy optimization

Authors:
Zhimin Yang;Xiao Yang;Bingquan Zhang
Affiliations:
Zhijiang College, Zhejiang University of Technology, Hangzhou, P.R. China;College of Business and Administration, Zhejiang University of Technology, Hangzhou, P.R. China;Zhijiang College, Zhejiang University of Technology, Hangzhou, P.R. China
Venue:
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Year:
2009

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Abstract

This paper is concerned with the fuzzy support vector classification, in which both of the type of the output training point and the value of the final fuzzy classification function are triangle fuzzy number. First, the fuzzy classification problem is formulated as a fuzzy chance constrained programming. Then, we transform this programming into its equivalence quadratic programming. Final, a fuzzy support vector classification algorithm is proposed to deal with the problem. An example is presented to illustrate rationality of the algorithm.