Robust Sparse Linear Discriminant Analysis

Linear discriminant analysis (LDA) is a very popular supervised feature extraction method and has been extended to different variants. However, classical LDA has the following problems: 1) The obtained discriminant projection does not have good interpretability for features; 2) LDA is sensitive to n...

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Bibliographic Details
Published in:IEEE transactions on circuits and systems for video technology 2019-02, Vol.29 (2), p.390-403
Main Authors: Wen, Jie, Fang, Xiaozhao, Cui, Jinrong, Fei, Lunke, Yan, Ke, Chen, Yan, Xu, Yong
Format: Article
Language:English
Subjects:
Data mining
data reconstruction
Discriminant analysis
Feature extraction
feature selection
Linear discriminant analysis
Noise sensitivity
Principal component analysis
Robustness
Sparse matrices
State of the art
Task analysis
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