SavedAdd your journal

Journals / Hacettepe Journal of Mathematics and Statistics / 2007 / Cilt: 36 - Sayı: 2

Data Envelopment Analysis Approach to Two-Group Classification Problems and an Experimental Comparison with some Classification Models

Hasan BAL
H. Hasan ÖRKCU
Pages
169–180
Publication Date
2022-10-18
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
🔖

Cite This Article

BAL, H., ÖRKCU, H. H. (2022). Data Envelopment Analysis Approach to Two-Group Classification Problems and an Experimental Comparison with some Classification Models. Hacettepe Journal of Mathematics and Statistics, Cilt: 36 - Sayı: 2, 169–180. https://ajindex.com/articles/530742

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (15)

  1. Anderson, T. W. An Introduction to Multivariate Statistical Analysis (Wiley, New York, 1984)
  2. Bajgier, S. M. and Hill, A. V. An experimental comparison of statistical and linear program- ming approaches to the discriminant problem, Decision Sciences 13, 604–618, 1982.
  3. Charnes A, Cooper W. W. and Rhodes E. Measuring the efficiency of decision making units, European Journal of Operational Research 2, 429–444, 1978.
  4. Cooper, W. W., Seiford, L. M. and Tone, K. Data Envelopment Analysis (Kluwer Academic Publishers, Boston, 2000). Farrell M. J. The measurement of productivity efficiency, Journal of Royal Statistical Society, Series A, CXX, 253–287, 1957.
  5. Fred, N. and Glover, F. Simple but powerful goal programming formulations for the statistical discriminant problem, European Journal of Operational Research 7, 44–60, 1981.
  6. Fred, N. and Glover, F. A linear programming approach to the discriminant problem, Deci- sion Sciences 12, 68–74, 1981.
  7. Fred, N. and Glover, F. Evaluating alternative linear programming models to solve the two- group discriminant problem, Decision Sciences 17, 589–585, 1986.
  8. Glen, J. J. A comparison of standard and two-stage mathematical programming discriminant analysis methods, European Journal of Operational Research 171, 496–515, 2006.
  9. Glover, F. Improved linear programming models for discriminant analysis, Decision Sciences 21, 771–785, 1990.
  10. Koehler, G. J. and Erenguc, S. S. Minimizing misclassifications in linear discriminant anal- ysis, Decision Sciences 21, 63–85, 1990.
  11. Lam, KF., Choo, E. U. and Moy, J. W. Minimizing deviations from the group mean: A new linear programming approach for The two-group classification problem, European Journal of Operational Research 88, 358–367, 1996. [13] Lam, KF. and Moy, J. W. Improved linear programming formulations for the multi-group discriminant problem, Journal of Operational Research Society 47, 1526–1529, 1996.
  12. Lam, KF. and Moy, J. W. An experimental comparison of some recently developed linear programming approaches to the discriminant problem, Computers and Operations Research 24(7), 593–599, 1997.
  13. Lam, KF. and Moy, J. W. Combining discriminant methods in solving classification prob- lems in two-group discriminant analysis, European Journal of Operational Research 138, 294–301, 2002.
  14. Ragsdale, C. T. and Stam, A. Mathematical programming formulations for the discriminant problem: An old dog does new tricks, Decision Sciences 22, 296–307, 1991.
  15. Retzlaff-Roberts, D. L. Relating discriminant analy