Weighted maximum margin discriminant analysis with kernels

A new kernel-based learning algorithm, called kernel weighted maximum margin discriminant analysis (KWMMDA), is presented in this paper. Different from the previous discriminant analysis algorithms based on the traditional Fisher discriminant criterion, KWMMDA is derived based on a new discriminant...

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Bibliographic Details
Published inNeurocomputing (Amsterdam) Vol. 67; pp. 357 - 362
Main Authors Zheng, Wenming, Zou, Cairong, Zhao, Li
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.08.2005
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Summary:A new kernel-based learning algorithm, called kernel weighted maximum margin discriminant analysis (KWMMDA), is presented in this paper. Different from the previous discriminant analysis algorithms based on the traditional Fisher discriminant criterion, KWMMDA is derived based on a new discriminant criterion, called weighted maximum margin criterion (WMMC). The better performance of KWMMDA is demonstrated by experiments on real data set.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2004.12.008