Abstract
Knowledge discovered from data tables is often presented in terms of “if... then...” decision rules. With each rule a confidence measure is associated. We present a method for measuring importance of each single condition or interactions among groups of conditions in the “if” part of the rules. The methodology is based on some indices introduced in literature to analyze fuzzy measures.
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References
Banzhaf, J. F., Weighted voting doesn’t work: A mathematical analysis, Rutgers Law Review, 19, 1965, 317–343.
Chateaneuf A., Jaffray, J., Some charactrtizations of Lower Probabilities and other Monotone Capacities through the use of Möbius Inversion, Mathematical Social Science, 17, 1989, 263–283
Grabisch M., The application of fuzzy integrals in muliticriteria decision making, European Journal of Operational Research, 89, 1996, 445–456.
Grabisch M., k-order additive discrete fuzzy measures and their representation, Fuzzy Sets and Systems, 89, 1997, 445–456.
Greco S., Matarazzo B., Slowinski R., Fuzzy measures as a technique for rough set analysis, in Proc. 6 th European Congress on Intelligent Techniques & Soft Computing (EUFIT’98), Aachen, September 7-10, 1998, 99–103.
Greco S., Matarazzo B., Slowinski R., The use of rough sets and fuzzy sets in MCDM, in T. Gal, T. Hanne and T. Stewart (eds.), Advances in Multiple Criteria Decision Making. Kluwer Academic Publishers, 1999, 14.1–14.59.
Murofushi T., Soneda S., Techniques for reading fuzzy measures (iii): interaction index, in Proc. 9th Fuzzy Systems Symposium, Sapporo, May 1993, 693–696, in Japanese.
Pawlak Z., Rough sets and decision algorithms, in Ziarko W., Yao Y.Y. (eds.), Proc. 2nd Int. Conf. on Rough Sets and Current Trends in Computing, Banff, October 16-19, 2000, 1–16.
Roubens, M., Interaction between criteria through the use of fuzzy measures, Report 96.007, Institut de Mathématique, Université de Liége, 1996.
Shapley L. S., A value for n-person games, in H. W. Kuhn, A. W. Tucker (eds.), Contributions to the Theory of Games II, Princeton University Press, Princeton, 1953, 307–317.
Stefanowski J., On rough set based approaches to induction of decision rules, in Polkowski L., Skowron A. (eds.), Rough sets in knowledge discovery, vol 1. Methodology and applications, Physica-Verlag, Heidelberg, 1998, 500–529.
Yao Y.Y., Zhong N., An analysis of quantitative measures associated with rules, in Proceedings of the Third Pacific-Asia Conference on Knowledge Discovery and Data Mining, LNAI 1574, Springer, 1999, 479–488.
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Greco, S., Matarazzo, B., Słowiński, R., Stefanowski, J. (2002). Importance and Interaction of Conditions in Decision Rules. In: Alpigini, J.J., Peters, J.F., Skowron, A., Zhong, N. (eds) Rough Sets and Current Trends in Computing. RSCTC 2002. Lecture Notes in Computer Science(), vol 2475. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45813-1_33
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DOI: https://doi.org/10.1007/3-540-45813-1_33
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