Generalized Nonlinear Discriminant Analysis

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.

• Type: Conference
• Year: 2008
• Where: ICPR
• Authors: Hua Zhang, Li Zhang, Licheng Jiao, Weida Zhou
• Keywords: Computer Vision, ICPR 2008, Mapping Space Corresponds, Nonlinear Discriminant Analysis, Nonlinear Mapping Space