LDA/QR: an efficient and effective dimension reduction algorithm and its theoretical foundation

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摘要

LDA/QR, a linear discriminant analysis (LDA) based dimension reduction algorithm is presented. It achieves the efficiency by introducing a QR decomposition on a small-size matrix, while keeping competitive classification accuracy. Its theoretical foundation is also presented.

论文关键词：Linear discriminant analysis,QR-decomposition,Pseudo-inverse

论文评审过程：Received 4 August 2003, Accepted 12 August 2003, Available online 20 February 2004.

论文官网地址：https://doi.org/10.1016/j.patcog.2003.08.006