• Corpus ID: 226246428

Capped norm linear discriminant analysis and its applications

@article{Liu2020CappedNL,
  title={Capped norm linear discriminant analysis and its applications},
  author={Jiakou Liu and Xiong Xiong and Pei-Wei Ren and Da Zhao and Chunna Li and Yuanhai Shao},
  journal={ArXiv},
  year={2020},
  volume={abs/2011.02147}
}
Classical linear discriminant analysis (LDA) is based on squared Frobenious norm and hence is sensitive to outliers and noise. To improve the robustness of LDA, in this paper, we introduce capped l_{2,1}-norm of a matrix, which employs non-squared l_2-norm and "capped" operation, and further propose a novel capped l_{2,1}-norm linear discriminant analysis, called CLDA. Due to the use of capped l_{2,1}-norm, CLDA can effectively remove extreme outliers and suppress the effect of noise data. In… 
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