Linear discriminant analysis for two classes via removal of classification structure

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37 Scopus citations


A new method for two-class linear discriminant analysis, called "removal of classification structure," is proposed. Its novelty lies in the transformation of the data along an identified discriminant direction into data without discriminant information and iteration to obtain the next discriminant direction. It is free to search for discriminant directions oblique to each other and ensures that the informative directions already found will not be chosen again at a later stage. The efficacy of the method is examined for two discriminant criteria. Studies with a wide spectrum of synthetic data sets and a real data set indicate that the discrimination quality of these criteria can be improved by the proposed method.

Original languageEnglish
Pages (from-to)187-192
Number of pages6
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number2
StatePublished - 1 Dec 1997


  • Dimension reduction
  • Discriminant plots
  • Exploratory data analysis
  • Linear discriminant analysis
  • Structure removal

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics


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