- Volume 10 Issue 1
In rough set literatures, methods for inducing minimal rules from a given decision table have been proposed. When the decision attribute is ordinal, inducing rules about upward and downward unions of decision classes is advantageous in the simplicity of obtained rules. However, because of independent applications of the rule induction method, inclusion relations among upward/downward unions in conclusion parts are not inherited to the condition parts of obtained rules. This non-inheritance may debase the quality of obtained rules. To ensure that inclusion relations among conclusions are inherited to conditions, we propose two rule induction approaches. The performances of the proposed approaches considering the inclusion relations between conclusions are examined by numerical experiments.
Rough Set;Rule Induction;Upward/Downward Union;MLEM2
- Furnkranz, J. (1999), Separate-and-conquer rule learning, Artificial Intelligence Review, 13, 3-54. https://doi.org/10.1023/A:1006524209794
- Greco, S., Matarazzo, B., and Słowinski, R. (1998), New developments in the rough set approach to multiattribute decision analysis, Bulletin of International Rough Set Society, 2, 57-87.
- Greco, S., Matarazzo, B., and Słowinski, R. (1999), Rough approximation of a preference relation by dominance relation, European Journal of Operational Research, 117, 63-83. https://doi.org/10.1016/S0377-2217(98)00127-1
- Greco, S., Matarazzo, B., and Słowinski, R. (2001), Rough sets theory for multicriteria decision analysis, European Journal of Operational Research, 129, 1-47. https://doi.org/10.1016/S0377-2217(00)00167-3
- Greco, S., Matarazzo, B., and Słowinski, R. (2002), Rough approximation by dominance relations, International Journal of Intelligent Systems, 17, 153-171. https://doi.org/10.1002/int.10014
- Grzymala-Busse, J. W. (1992), LERS-A system for learning from examples based on rough sets, In R. Słowinski (ed.), Intelligent Decision Support: Handbook of Application and Advances of the Rough Set Theory (Dordrecht:Kluwer Academic Publishers), 3-18.
- Grzymala-Busse, J. W. (2003), MLEM2-discretization during rule induction, In M. A. Klopotek, S. T. Wierzchon, K. Trojanowski (eds.), Proceedings of the International IIS: IIPWM'03 Conference, Zakopane, Poland (Berlin Heidelberg: Springer-Verlag), 499-508.
- Hoover, K. D. and Perez, S. J. (1999), Data mining reconsidered: encompassing and the general-tospecific approach to specification search, Econometrics Journal, 2, 167-191. https://doi.org/10.1111/1368-423X.00025
- Wikipedia Rule Induction (web) http://en.wikipedia.org/wiki/Rule_induction.
- Pawlak, Z. (1982), Rough sets, International Journal of Information Computer Science, 11, 341-356. https://doi.org/10.1007/BF01001956
- Pawlak, Z. (1991), Rough sets: Theoretical Aspects of Reasoning about Data, Kluwer Academic Publishing, Dordrecht.
- Stefanowski, J. (1988), Rough set based rule induction techniques for classification problems, In Proceedings of 6th European Congress on Intelligent Techniques and Soft Computing, Aachen, Germany, 1, 109-113.