Combining discriminant methods in solving classification problems in two-group discriminant analysis

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Pages (from-to)294-301
Journal / PublicationEuropean Journal of Operational Research
Volume138
Issue number2
Publication statusPublished - 16 Apr 2002

Abstract

As no single-discriminant method outperforms other discriminant methods under all circumstances, decision-makers may solve a classification problem using several discriminant methods and examine their performance for classification purposes in the training sample. Based on this performance, better classification methods might be adopted and poor methods might be avoided. However, which single-discriminant method is best to predict the classification of new observations is still not clear, especially when some methods offer a similar classification performance in the training samplae. In this paper, we present a method that combines several discriminant methods to predict the classification of new observations. Simulation experiments are run to test this combining technique. © 2002 Elsevier Science B.V. All rights reserved.

Research Area(s)

  • Classification, Combining, Discriminant analysis, Goal programming, Linear programming, Multivariate statistics