Direct minimization of error rates in multivariate classification - Michael C. Röhl; Claus Weihs (Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, 1999)
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.
Keywords: 519; classification; discriminant analysis; error rate; simulated annealing; user requests