Mathematical programming based heuristics for improving LP-generated classifiers for the multiclass supervised classification problem

European Journal of Operational Research

Volumn 168, Issue 1, 2006, Pages 181-199

  Adem, Jan ^a   Gochet, Willy ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

Heuristics; Mixed integer linear programming; Supervised classification

Indexed keywords

APPROXIMATION THEORY; CLASSIFICATION (OF INFORMATION); COMPUTER SIMULATION; INTEGER PROGRAMMING; LINEAR PROGRAMMING; NEURAL NETWORKS; PROBLEM SOLVING; SERVERS; TREES (MATHEMATICS); VECTORS;

CRUDE APPROXIMATIONS; DATASETS; MIXED INTEGER LINEAR PROGRAMMING; SUPERVIZED CLASSIFICATION;

HEURISTIC METHODS;

EID: 16244403637     PISSN: 03772217     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ejor.2004.04.031     Document Type: Article

References (27)

1. S.M. Bajgier, and A.V. Hill An experimental comparison of statistical and linear programming approaches to the discriminant problem Decision Sciences 13 1982 604 618
2. W.J. Banks, and P.L. Abad An efficient optimal solution algorithm for the classification problem Decision Sciences 22 1991 1008 1023
3. K.P. Bennett, and O.L. Mangasarian Multicategory discrimination via linear programming Optimization Methods and Software 3 1993 27 39
4. K.P. Bennet, and E.J. Bredensteiner A parametric optimization method for machine learning INFORMS Journal on Computing 19 3 1997 311 318
5. C.L. Blake, C.J. Merz, UCI Repository of machine learning databases [ http://www.ics.uci.edu/~mlearn/MLRepository.html ]. Department of Information and Computer Science, University of California, Irvine, CA, 1998
6. J.W. Chinneck Fast heuristics for the maximum feasible subsystem problem INFORMS Journal on Computing 13 3 2001 210 223
7. R.O. Duda, P.E. Hart, and D.H. Strok Pattern Recognition second ed. 2001 Wiley-Interscience New York
8. S.S. Erenguc, and G.J. Koehler Survey of mathematical programming models and experimental results for linear discriminant analysis Managerial and Decision Economics 11 1990 215 225
9. N. Freed, and F. Glover Simple but powerful goal programming models for discriminant problems European Journal of Operational Research 7 1981 44 60
10. W.V. Gehrlein General mathematical programming formulations for the statistical classification problem Operations Research Letters 5 6 1986 299 304
11. W. Gochet, A. Stam, V. Srinivasan, and S. Chen Multigroup discriminant analysis using linear programming Operations Research 45 2 1997 213 225
12. D.J. Hand Construction and Assessment of Classification Rules 1997 John Wiley Chichester
13. T. Hastie, R. Tibshirani, and J. Friedman The Elements of Statistical Learning 2001 Springer
14. G.J. Koehler Linear discriminant functions determined by genetic search ORSA Journal on Computing 3 4 1991 345 357
15. G.J. Koehler, and S.S. Erenguc Minimizing misclassifications in linear discriminant analysis Decision Sciences 21 1990 63 85
16. J.M. Liittschwager, and C. Wang Integer programming solution of a classification problem Management Science 24 14 1978 1515 1525
17. T. Lim, W. Loh, and Y. Shih A comparison of prediction accuracy, complexity, and training time of thirty-three old and new classification algorithms Machine Learning 40 2000 203 229
18. P. Marcotte, G. Marquis, and G. Savard A new implicit enumeration scheme for the discriminant analysis problem Computers Operations Research 22 6 1995 625 639
19. P.A. Rubin Heuristic solution procedures for a mixed-integer programming discriminant model Managerial and Decision Economics 11 1990 255 266
20. P.A. Rubin Solving mixed integer classification problems by decomposition Annals of Operations Research 74 1997 51 64
21. L. Schrage LINDO: Optimization Software for Linear Programming 1995 Lindo Systems Chicago, IL
22. R.C. Soltysik, and P.R. Yarnold The Warmack-Gonzalez algorithm for linear two-category multivariable optimal discriminant analysis Computers Operations Research 21 7 1994 735 745
23. A. Stam, and E.A. Joachimsthaler A comparison of a robust mixed-integer approach to existing methods for establishing classification rules for the discriminant problem European Journal of Operations Research 46 1 1990 113 122
24. D. Tax, and R. Duin Using two-class classifiers for multiclass classification. Proceedings 16th International Conference on Pattern Recognition, Quebec City, Canada vol. II 2002 IEEE Computer Society Press Los Alamitos 124 127
25. T. Van Gestel, J. Suykens, B. Baesens, S. Viaene, J. Vanthienen, G. Dedene, B. De Moor, J. Vandewalle, Benchmarking least squares support vector machine classifiers, Machine Learning, forthcoming
26. V.N. Vapnik Statistical Learning Theory 1998 John Wiley New York
27. A. Webb Statistical Pattern Recognition 1999 Arnold London London