A note on kernel uncorrelated discriminant analysis
作者：
Highlights：
•
摘要
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.
论文关键词：Kernel uncorrelated discriminant analysis (KUDA),Degenerate eigenvalue problem,Generalized discriminant analysis
论文评审过程：Received 27 December 2004, Accepted 10 January 2005, Available online 26 April 2005.
论文官网地址：https://doi.org/10.1016/j.patcog.2005.01.022
