Complete Kernal Fisher Discrimination Analysis

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Author(s): David Zhang (Hong Kong Polytechnic University, Hong Kong), Xiao-Yuan Jing (ShenZhen Graduate School of Harbin Institute of Technology, China)and Jian Yang (Hong Kong Polytechnic University, Hong Kong)
Copyright: 2006
Pages: 23
Source title: Biometric Image Discrimination Technologies: Computational Intelligence and its Applications Series
Source Author(s)/Editor(s): David Zhang (Hong Kong Polytechnic University, Hong Kong ), Xiao-Yuan Jing (ShenZhen Graduate School of Harbin Institute of Technology, China)and Jian Yang (Hong Kong Polytechnic University, Hong Kong)
DOI: 10.4018/978-1-59140-830-7.ch010

Keywords: Bioinformatics / Biometrics / Medical Information Science Reference / Medicine & Healthcare

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Abstract

This chapter introduces a complete kernel Fisher discriminant analysis (KFD) that is a useful statistical technique applied to biometric application. We first describe theoretical perspective of KPCA. Then, a new KFD algorithm framework, KPCA plus LDA, is given. Afterwards, we discuss the complete KFD algorithm. Finally, the experimental results and chapter summary are given.

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