Classification by vertical and cutting multi-hyperplane decision tree induction

Decision Support Systems

Volumn 48, Issue 3, 2010, Pages 430-436

  Better, Marco ^a   Glover, Fred ^a   Samorani, Michele ^b  

^a OptTek Systems Inc   (United States)

^b UNIVERSITY OF COLORADO   (United States)

Author keywords

Data mining; Discrimination analysis; Mathematical programming; Piecewise linear models

Indexed keywords

CLASSIFICATION ACCURACY; COMPUTATIONAL RESULTS; DATA MINING APPLICATIONS; DECISION TREE INDUCTION; DISCRIMINATION ANALYSIS; GROUP CLASSIFICATION; MIXED INTEGER PROGRAMMING; PIECEWISE-LINEAR MODELS; SEPARATING HYPERPLANE;

DATA HANDLING; DECISION TREES; FLUORINE CONTAINING POLYMERS; GEOMETRY; MATHEMATICAL MODELS; PIECEWISE LINEAR TECHNIQUES;

INTEGER PROGRAMMING;

EID: 72249092677     PISSN: 01679236     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.dss.2009.06.004     Document Type: Article

References (27)

1. Abad P.L., and Banks W.J. New LP based heuristics for the classification problem. European Journal of Operational Research 67 (1993) 88-100
2. Bennett K.P., and Blue J.A. A support vector machine approach to decision trees. In: Blue J.A. (Ed). Proceedings of the IEEE World Congress on Computational Intelligence (1998), Anchorage, AK, USA 2396-2401
3. Charnes A., and Cooper W.W. Management models and industrial applications of linear programming (1961), Wiley, New York
4. Charnes A., Cooper W.W., and Ferguson R.O. Optimal estimation of executive compensation by linear programming. Management Science 1 (1955) 138-151
5. Chau M., and Chen H. A machine learning approach to web page filtering using content and structure analysis. Decision Support Systems 44 (2008) 482-494
6. Cheung K., Kwok J.T., Law M., and Tsui K. Mining customer product ratings for personalized marketing. Decision Support Systems 35 (2003) 231-243
7. Cristianini N., and Shawe-Taylor J. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods (2000), Cambridge University Press, New York
8. Feelders A.J. Statistical Concepts, Intelligent Data Analysis (2003), Springer-Verlag New York, Inc., New York
9. Freed N., and Glover F. Simple but powerful goal programming models for discriminant problems. European Journal of Operational Research 7 (1981) 44-60
10. Glen J.J. Integer programming methods for normalisation and variable selection in mathematical programming discriminant analysis models. Journal of the Operational Research Society 50 (1999) 1043-1053
11. Glen J.J. An iterative mixed integer programming method for classification accuracy maximizing discriminant analysis. Computers & Operations Research 30 (2003) 181-198
12. Glen J.J. Mathematical programming models for piecewise-linear discriminant analysis. Journal of the Operational Research Society 56 (2004) 331-341
13. Glover F. Improved linear programming models for discriminant analysis*. Decision Sciences 21 (1990) 771-785
14. Glover F., Kochenberger G., and Better M. Improved Classification and Discrimination by Successive Hyperplane and Multi-hyperplane Separation, Working Paper (2006), University of Colorado, Boulder, Boulder
15. Han J., and Kamber M. Data Mining: Concepts and Techniques (2000), Morgan Kaufmann Publishers Inc., San Francisco, CA
16. Ince H., and Trafalis T.B. A hybrid model for exchange rate prediction. Decision Support Systems 42 (2006) 1054-1062
17. Li X. A scalable decision tree system and its application in pattern recognition and intrusion detection. Decision Support Systems 41 (2005) 112-130
18. Murthy S.K., Kasif S., and Salzberg S. A system for the induction of oblique decision trees. Journal of Artificial Intelligence Research 2 (1994) 1-32
19. Peng Y., Kou G., Shi Y., and Chen Z. A multi-criteria convex quadratic programming model for credit data analysis. Decision Support Systems 44 (2008) 1016-1030
20. Quinlan J.R. Induction of decision trees. Machine Learning 1 (1986) 81-106
21. Rokach L., and Maimon O. Top-down induction of decision trees classifiers - a survey. IEEE Transactions on Systems, Man, and Cybernetics Part C: Applications and Reviews 35 (2005) 476-487
22. Stam A., and Ragsdale C.T. On the classification gap in mathematical programming-based approaches to the discriminant problem. Naval Research Logistics 39 (1992) 545-559
23. Sueyoshi T. Extended DEA-discriminant analysis. European Journal of Operational Research 131 (2001) 324-351
24. Sueyoshi T., and Goto M. DEA-DA for bankruptcy-based performance assessment: misclassification analysis of Japanese Construction Industry. European Journal of Operational Research 199 (2009) 579-594
25. T. Sueyoshi, M. Goto, Methodological Comparison between DEA (Data Envelopment Analysis) and DEA-DA (Discriminant Analysis) from the perspective of bankruptcy assessment, European Journal of Operational Research, Accepted Manuscript 199 (2009) 561-575.
26. Sun M., and Xiong M. A mathematical programming approach for gene selection and tissue classification. Bioinformatics 19 (2003) 1243-1251
27. Witten I.H., and Frank E. Data mining: practical machine learning tools and techniques (2005), Morgan Kaufman, Boston, MA