Rapid and brief communication: Nonlinear discriminant mapping using the Laplacian of a graph

Authors:
Hong Tang;Tao Fang;Peng-Fei Shi
Affiliations:
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200030, PR China;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200030, PR China;Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200030, PR China
Venue:
Pattern Recognition
Year:
2006

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Abstract

In this paper, an algorithm for nonlinear discriminant mapping (NDM) is presented, which elegantly integrates the ideas of both linear discriminant analysis (LDA) and Isomap by using the Laplacian of a graph. The objective of NDM is to find a linear subspace project of nonlinear data set, which preserves maximum difference between between-class scatter and within-class scatter.