Direct minimization of error rates in multivariate classification
type: Item
instance of: scholarly article
title: Direct minimization of error rates in multivariate classification
zbMATH Open document ID: 1009.65002
author: Michael C. Röhl
author: Claus Weihs
author: Winfried Theis
published in: Computational Statistics
publication date: 2003-02-06T00:00:00Z
full work available at URL: http://hdl.handle.net/2003/4933
review text: The authors propose and discusse two versions of a computer intensive method for linear dimension reduction that minimize the classification error directly. The method is based on a powerful modern optimization technique (simulated annealing optimization algorithm) and is a flexible tool for incorporating user preferences. Simulation and a real world example demonstrate the superiority of the proposed methods over the classical discriminant analysis. Special emphasis is given to the case when discriminant analysis collapses.
Mathematics Subject Classification ID: 62-08
Mathematics Subject Classification ID: 62H30
zbMATH DE Number: 1865437
zbMATH Keywords: classification
zbMATH Keywords: discriminant analysis
zbMATH Keywords: error rate
zbMATH Keywords: simulated annealing
zbMATH Keywords: user preferences
zbMATH Keywords: dimension reduction
MaRDI profile type: Publication
OpenAlex ID: W1518324071
cites work: Generalized Simulated Annealing for Function Optimization
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cites work: Q5289008
DOI: 10.1007/S001800200089
description: scientific article; zbMATH DE number 1865437