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Evaluation of an adaptive discriminant procedure

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  • Carol Markowski
  • Edward Markowski

Abstract

This paper reports the results of a simulation study comparing Fisher's Linear Discriminant Function, Smith's Quadratic Discriminant Function, a nonparametric Nearest Neighbor approach, a linear programming approach, and a new adaptive statistical method for solving the discriminant problem. The study examines the two-group discriminant problem with four variables, of which two are continuous and two are discrete. The analysis is based on the rate of misclassification using each method. The results indicate that the adaptive method is an effective alternative to existing methods and that the adaptive philosophy of using the training sample to identify which of several methods should be applied to the validation sample merits further study. Copyright Kluwer Academic Publishers 1997

Suggested Citation

  • Carol Markowski & Edward Markowski, 1997. "Evaluation of an adaptive discriminant procedure," Annals of Operations Research, Springer, vol. 74(0), pages 211-222, November.
    • Handle: RePEc:spr:annopr:v:74:y:1997:i:0:p:211-222:10.1023/a:1018970304612
    DOI: 10.1023/A:1018970304612
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    Cited by:

    1. Pavur, Robert, 2002. "A comparative study of the effect of the position of outliers on classical and nontraditional approaches to the two-group classification problem," European Journal of Operational Research, Elsevier, vol. 136(3), pages 603-615, February.
    2. Lam, Kim Fung & Moy, Jane W., 2002. "Combining discriminant methods in solving classification problems in two-group discriminant analysis," European Journal of Operational Research, Elsevier, vol. 138(2), pages 294-301, April.

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