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Discrimination Based on the Atypicity Index versus Density Function Ratio

  • H. Chamlal
  • S. Slaoui Chah
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

We propose a method of discrimination, based on the atypicity index and the density function. After a short survey of the atypicity index, we show that the presence of “critical regions”, when we apply the bayesian quadratic discrimination, under some hypotheses, leads to misclassifications. The performance of the proposed method versus quadratic and linear discrimination is assessed via simulation. It is generally shown that the discrimination based on the ratio (atypicity index/density function) consistently yields noticeably higher percentage of well classified individuals relative to the traditional methods. The method is illustrated with a numerical example and is compared to quadratic discrimination

Keywords

Prior Probability Critical Region Quadratic Discriminant Analysis Linear Discriminant Function Linear Discrimination 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin · Heidelberg 2000

Authors and Affiliations

  • H. Chamlal
    • 1
  • S. Slaoui Chah
    • 1
  1. 1.Département de Mathématiques et InformatiqueFaculté des SciencesRabat-MarocMorocco

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