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Direct minimization of error rates in multivariate classification

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  • Röhl, Michael C.
  • Weihs, Claus

Abstract

We propose a computer intensive method for linear dimension reduction which minimizes the classification error directly. Simulated annealing (Bohachevsky et al 1986) as a modern optimization technique is used to solve this problem effectively. This approach easily allows to incorporate user requests by means of penalty terms. Simulations demonstrate the superiority of optimal classification to classical discriminant analysis (McLachlan 1992). Special emphasis is put on the case when discriminant analysis collapses.

Suggested Citation

  • Röhl, Michael C. & Weihs, Claus, 1999. "Direct minimization of error rates in multivariate classification," Technical Reports 1999,43, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:199943
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    References listed on IDEAS

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    1. Polzehl, Jorg, 1995. "Projection pursuit discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 20(2), pages 141-157, August.
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