Using model trees for classification

Machine Learning

Volumn 32, Issue 1, 1998, Pages 63-76

  Frank, Eibe ^a   Wang, Yong ^a   Inglis, Stuart ^a   Holmes, Geoffrey ^a   Witten, Ian H ^a  

^a UNIVERSITY OF WAIKATO   (New Zealand)

Author keywords

C5.0; Classification algorithms; Decision trees; M5; Model trees

Indexed keywords

CLASSIFICATION (OF INFORMATION); DECISION MAKING; FUNCTIONS; LEARNING SYSTEMS; MATHEMATICAL TRANSFORMATIONS; NUMERICAL METHODS; PROBLEM SOLVING; REGRESSION ANALYSIS; ALGORITHMS; APPROXIMATION THEORY; DECISION THEORY; MATHEMATICAL MODELS; TREES (MATHEMATICS);

C5.0; CLASSIFICATION ALGORITHMS; DECISION TREES; M5; MODEL TREES; LINEAR REGRESSION FUNCTIONS;

TREES (MATHEMATICS); PATTERN RECOGNITION;

EID: 0032117676     PISSN: 08856125     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1007421302149     Document Type: Article

References (10)

1. Breiman, L., Friedman, J.H., Olshen, R.A. & Stone, C.J. (1984). Classification and regression trees. Belmont CA: Wadsworth.
2. Devroye, L., Gyoerfi, L. & Lugosi, G. (1996). A probabilistic theory of pattern recognition. New York: Springer-Verlag.
3. Dietterich, T.G. & Bakiri G. (1995). "Solving multiclass learning problems via error-correcting output codes," Journal of AI research, 2, 263-286.
4. Holte, R.C. (1993). "Very simple classification rules perform well on most commonly used datasets," Machine Learning, 11, 63-91.
5. Merz, C.J. & Murphy, P.M. (1996). UCI Repository of machine learning data-bases [http://www. ics.uci.edu/~mlearn/MLRepository.html]. Irvine, CA: University of California, Department of Information and Computer Science.
6. Quinlan, J.R. (1992). "Learning with continuous classes," Proceedings Australian Joint Conference on Artificial Intelligence (pp. 343-348). World Scientific, Singapore.
7. Quinlan, J.R. (1993). C4.5: Programs for machine learning. Morgan Kaufmann.
8. Smyth, P., Gray, A. & Fayyad, U. (1995). "Retrofitting Decision tree classifiers using Kernel Density Estimation," Proceedings International Conference on Machine Learning (pp. 506-514). San Francisco, CA: Morgan Kaufmann.
9. Torgo, L. (1997). "Kernel Regression Trees," Proceedings of the poster papers of the European Conference on Machine Learning. University of Economics, Faculty of Informatics and Statistics, Prague.
10. Wang, Y. & Witten, I.H. (1997). "Induction of model trees for predicting continuous classes," Proceedings of the poster papers of the European Conference on Machine Learning, University of Economics, Faculty of Informatics and Statistics, Prague.