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Experimental evaluation of the classificatory performance of mathematical programming approaches to the three-group discriminant problem: The case of small samples.

Authors :
Loucopoulos, Constantine
Pavur, Robert
Source :
Annals of Operations Research; 1997, Vol. 74 Issue 1-4, p191-209, 19p
Publication Year :
1997

Abstract

Although there have been several journal articles on the classificatory performance of mathematical programming approaches to the two-group discriminant problem, there has been no simulation study on the classificatory performance of mathematical programming approaches to the multiple-group problem reported in the literature. This study reports the results of a simulation experiment on the classificatory performance of a single-function and a multiple-function mathematical programming model relative to that of the standard parametric procedures for the three-group problem with small training samples. The effect of second-order terms on the classificatory performance of the mathematical programming models for the three-group problem is also investigated. Furthermore, this study theoretically examines the range of parameter values of a multiple-function mathematical programming model for which its number of misclassifications in the training sample cannot exceed that of a single-function model. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02545330
Volume :
74
Issue :
1-4
Database :
Complementary Index
Journal :
Annals of Operations Research
Publication Type :
Academic Journal
Accession number :
18668484
Full Text :
https://doi.org/10.1023/A:1018918320541