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	Multi-class SVM classifier based on pairwise coupling
	Li, ZY ; Tang, SW ; Yan, SC
	2002
英文摘要	In this paper, a novel structure is proposed to extend standard support vector classifier to multi-class cases. For a K-class classification task, an array of K optimal pairwise coupling classifier (O-PWC) is constructed, each of which is the most reliable and optimal for the corresponding class in the sense of cross entropy or square error. The final decision will be produced through combining the results of these K O-PWCs. The accuracy rate is improved while the computational cost will not increase too much. Our approach is applied to two applications: handwritten digital recognition on MNIST database and face recognition on Cambridge ORL face database, experimental results reveal that our method is effective and efficient.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000187252200025&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Computer Science, Artificial Intelligence; Computer Science, Theory & Methods; SCI(E); CPCI-S(ISTP); 10
语种	英语
出处	SCI
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/291571]
专题	数学科学学院 信息科学技术学院
推荐引用方式 GB/T 7714	Li, ZY,Tang, SW,Yan, SC. Multi-class SVM classifier based on pairwise coupling. 2002-01-01.

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