Rapid and Brief Communication: A note on kernel uncorrelated discriminant analysis

Authors:
Wenming Zheng
Affiliations:
Research Center for Learning Science, Southeast University, Nanjing, Jiangsu 210096, PR China
Venue:
Pattern Recognition
Year:
2005

Citing 2
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MMM'07 Proceedings of the 13th International conference on Multimedia Modeling - Volume Part II

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Abstract

In this paper, we give a theoretical analysis on kernel uncorrelated discriminant analysis (KUDA) and point out the drawbacks underlying the current KUDA algorithm which was recently introduced by Liang and Shi [Pattern Recognition 38(2) (2005) 307-310]. Then we propose an effective algorithm to overcome these drawbacks. The effectiveness of the proposed method was confirmed by experiments.