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

被引：0
作者：
Constantine Loucopoulos
Robert Pavur
机构：
来源：
Annals of Operations Research | 1997年 / 74卷
关键词：
integer programming; discriminant analysis; simulation;
D O I：
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学科分类号：
摘要：
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.
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页码：191 / 209
页数：18
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