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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

Author

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  • Constantine Loucopoulos
  • Robert Pavur

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. Copyright Kluwer Academic Publishers 1997

Suggested Citation

  • Constantine Loucopoulos & Robert Pavur, 1997. "Experimental evaluation of the classificatory performance of mathematical programming approaches to the three-group discriminant problem: The case of small samples," Annals of Operations Research, Springer, vol. 74(0), pages 191-209, November.
    • Handle: RePEc:spr:annopr:v:74:y:1997:i:0:p:191-209:10.1023/a:1018918320541
    DOI: 10.1023/A:1018918320541
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    Cited by:

    1. Mingue Sun, 2009. "Liquidity Risk and Financial Competition: A Mixed Integer Programming Model for Multiple-Class Discriminant Analysis," Working Papers 0102, College of Business, University of Texas at San Antonio.
    2. Alina Mihaela Dima & Simona Vasilache, 2016. "Credit Risk modeling for Companies Default Prediction using Neural Networks," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 127-143, September.
    3. Loucopoulos, Constantine, 2001. "Three-group classification with unequal misclassification costs: a mathematical programming approach," Omega, Elsevier, vol. 29(3), pages 291-297, June.

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