Rapid and brief communications: Modified linear discriminant analysis

Authors:
Songcan Chen;Daohong Li
Affiliations:
Department of Computer Science & Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing 210016, China;Department of Computer Science & Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing 210016, China
Venue:
Pattern Recognition
Year:
2005

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Abstract

In this paper, a modified Fisher linear discriminant analysis (FLDA) is proposed and aims to not only overcome the rank limitation of FLDA, that is, at most only finding a discriminant vector for 2-class problem based on Fisher discriminant criterion, but also relax singularity of the within-class scatter matrix and finally improves classification performance of FLDA. Experiments on nine publicly available datasets show that the proposed method has better or comparable performance on all the datasets than FLDA.