Generalized Nonlinear Discriminant Analysis

被引：0

作者：

Zhang, Li ^{[1
]}

Zhou, Wei-Da ^{[1
]}

Zhang, Hua ^{[1
]}

Jiao, Li-Cheng ^{[1
]}

机构：

[1] Xidian Univ, Inst Intelligence Informat Proc, Xian 710071, Peoples R China

来源：

19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6 | 2008年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A Generalized Nonlinear Discriminant Analysis (GNDA) method is proposed, which implements Fisher discriminant analysis in a nonlinear mapping space. Linear discriminant analysis in the nonlinear mapping space corresponds to nonlinear discriminant analysis in an input space. GNDA suggests a unified framework of nonlinear discriminant analysis which includes the kernel Fisher discriminant analysis as a specific case. Experimental results on UCI data sets demonstrate the validity of our method.

引用

页码：2581 / 2584

页数：4

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