EVALUATING ALTERNATIVE LINEAR PROGRAMMING MODELS TO SOLVE THE TWO-GROUP DISCRIMINANT PROBLEM
| Autor: | Ned Freed, Fred Glover |
|---|---|
| Rok vydání: | 1986 |
| Předmět: |
Mathematical optimization
Class (computer programming) Information Systems and Management Linear programming Group (mathematics) Strategy and Management Boundary (topology) Linear discriminant analysis General Business Management and Accounting Variety (cybernetics) Discriminant Management of Technology and Innovation Goal programming Mathematics |
| Zdroj: | Decision Sciences. 17:151-162 |
| ISSN: | 1540-5915 0011-7315 |
| DOI: | 10.1111/j.1540-5915.1986.tb00218.x |
| Popis: | The two-group discriminant problem has applications in many areas, for example, differentiating between good credit risks and poor ones, between promising new firms and those likely to fail, or between patients with strong prospects for recovery and those highly at risk. To expand our tools for dealing with such problems, we propose a class of nonpara-metric discriminant procedures based on linear programming (LP). Although these procedures have attracted considerable attention recently, only a limited number of computational studies have examined the relative merits of alternative formulations. In this paper we provide a detailed study of three contrasting formulations for the two-group problem. The experimental design provides a variety of test conditions involving both normal and nonnormal populations. Our results establish the LP model which seeks to minimize the sum of deviations beyond the two-group boundary as a promising alternative to more conventional linear discriminant techniques. |
| Databáze: | OpenAIRE |
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