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A Review of Classification Models Using Discrete Variables

Author Affiliations

  • 1Department of Statistics, Nnamdi Azikiwe University, Awka NIGERIA
  • 2Department of Statistics, Nnamdi Azikiwe University, Awka NIGERIA
  • 3Department of Statistics, Imo State University, Owerri, NIGERIA
  • 4Department of Statistics, Federal University of Technology Owerri NIGERIA

Res. J. Mathematical & Statistical Sci., Volume 1, Issue (8), Pages 28-38, September,12 (2013)

Abstract

This paper is a review of the classification models used for discrete variables. Nine classification procedures for binary variables are discussed and some of them evaluated at each of 118 configurations of the sampling experiments. The results obtained ranked the procedures as follows: Optimal, first order Bahadur, LDF, Second Order, Full, Distance, Nrule.

References

  1. Cochran W.G. and Hopkins C.E., Some classification problems with multivariate qualitative data, Biometrics, 17, 10-32(1961)
  2. Gilbert E.S., on discriminant using qualitative variables, J. Ame. Stat. Ass., 63, 1399 (1968)
  3. Glick N., Sample base multinomial classification, Biometrics, 29, 241-256 (1973)
  4. Goldstein M. and Dillon W.R., Discrete discriminant analysis. John Wiley and Sons Inc. New York, (1978)
  5. Goldstein and Rabinowitz, Selection of variables for the two group multinomial classification, J .Ame. Stat. Ass., 70, 776-781(1975)
  6. Goldstein M. and Wolf E., On the problem of bias in multinomial classification, Biometrics, 33, 325-331 (1977)
  7. Hoel M. and Paterson C., A solution to the problem of optimum classification, Ann Math Stat., 20, 433-438 (1949)
  8. Hills M., Discriminant and Allocation with discrete data, J. Royal Statistical Society, C16, 237-250 (1967)
  9. Mclachlan R., Discriminant Analysis and Statistical Pattern Recognition, John Wiley and Sons Inc, New York (1992)