Direct Minimization of Error Rates in Multivariate Classification

Michael C. Röhl, Claus Weihs () and Winfried Theis
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Michael C. Röhl: Königstein/Ts.
Claus Weihs: Universität Dortmund
Winfried Theis: Universität Dortmund

Computational Statistics, 2002, vol. 17, issue 1, No 3, 29-46

Abstract: Summary We propose a computer intensive method for linear dimension reduction that minimizes the classification error directly. Simulated annealing (Bohachevsky et al. 1986), a modern optimization technique, is used to solve this problem effectively. This approach easily allows user preferences to be incorporated by means of penalty terms. Simulations and a real world example demonstrate the superiority of this optimal classification to classical discriminant analysis (McLachlan 1992). Special emphasis is given to the case when discriminant analysis collapses.

Keywords: classification; discriminant analysis; error rate; simulated annealing; user preferences (search for similar items in EconPapers)
Date: 2002
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s001800200089

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