Constructing decision trees with multiple response variables

International Journal of Management and Decision Making

Volumn 4, Issue 4, 2003, Pages 337-353

  Kim, Seong Jun ^a   Bae Lee, Kang ^b  

^a Gangneung Wonju National University   (South Korea)

^b Catholic University of Pusan   (South Korea)

Author keywords

data mining; decision tree; multiple response variables; node splitting criteria

Indexed keywords

EID: 84961562848     PISSN: 14624621     EISSN: 17415187     Source Type: Journal    
DOI: 10.1504/IJMDM.2003.003998     Document Type: Article

References (9)

1. Bose, I. and Mahapatra, R.K. (2001) ‘Business data mining - a machine learning perspective’, Information & Management, Vol. 39, pp.211–225.
2. Han, J. and Kamber, M. (2001) Data Mining - Concepts and Techniques, San Francisco, CA: Morgan Kaufmann.
3. Langley, P. and Simon, H.A. (1995) ‘Applications of machine learning and rule induction’, Communications of the ACM, Vol. 38, No. 11, pp.55–64.
4. Stark, K.D.C. and Pfeiffer, D.U. (1999) ‘The application of non-parametric techniques to solve classification problems in complex data sets in veterinary epidemiology - an example’, Intelligent Data Analysis, Vol. 3, pp.23–35.
5. Breiman, L., Friedman, J.H., Olshen, R.A. and Stone, C.J. (1998) Classification and Regression Trees, Boca Raton, FL: Chapman & Hall/CRC.
6. Chae, Y.M., Ho, S.H., Cho, K.W., Lee, D.H. and Ji, S.H. (2001) ‘Data mining approach to policy analysis in a health insurance domain’, International Journal of Medical Informatics, Vol. 62, pp.103–111.
7. Zhang, H. (1998) ‘Classification trees with multiple binary responses’, Journal of the American Statistical Association, Vol. 93, No. 441, pp.180–193.
8. Siciliano, R. and Mola, F. (2000) ‘Multivariate data analysis and modeling through classification and regression trees’, Computational Statistics & Data Analysis, Vol. 32, pp.285–301.
9. Brown, D.E., Pittard, C.L. and Park, H. (1996) ‘Classification trees with optimal multivariate decision nodes’, Pattern Recognition Letters, Vol. 17, pp.699–703.