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Robust Principal Component Analysis

Robust PCA is as the name implies a more robust version of PCA. Extremely useful for large but sparse datasets (many biological areas e.g. ecology, metabolomics, transcriptomics; and computer science e.g. visual recognition).
Provides a PCA which is less susceptible to outliers.

  • Guest
  • Sep 14 2016
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  • Massimo Cealti commented
    September 22, 2016 06:59

    agree, it is useful in other areas as well