Rough sets: current and future developments

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Expert SystemsVolume 20, Issue 5 p. 247-250 Free Access Rough sets: current and future developments Bruce Curry, Bruce Curry Cardiff Business SchoolSearch for more papers by this author Bruce Curry, Bruce Curry Cardiff Business SchoolSearch for more papers by this author First published: 10 October 2003 https://doi.org/10.1111/1468-0394.00248Citations: 2AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat References An, A., N. Shan, C. Chan, N. Cercone and W. Ziarko (1996) Discovering rules for water demand prediction: an enhanced rough-set approach, Engineering Applications of Artificial Intelligence, 9 (6), 645– 653. Bazan, J.G. (1998) A comparison of dynamic and non-dynamic rough set methodologies for extracting laws from decision tables, in Rough Sets in Knowledge Discovery 1: Methodology and Applications, L. Polkowski and A. Skowron (eds), Studies in Fuzziness and Soft Computing, Vol. 18, Heidelberg: Physica, Ch. 17, pp. 321– 365. Beynon, M., B. Curry and P. Morgan (2000) Classification and rule induction using rough set theory, Expert Systems, 17 (3), 136– 148. Chmielewski, M.R. and J.W. Grzymala-Busse (1996) Global discretization of continuous attributes as preprocessing for machine learning, International Journal of Approximate Reasoning, 15, 319– 331. Curry, B. (2003) Sampling aspects of rough set theory, Computational Management Science, forthcoming; copy available from the author. Duda, R.O., P.E. Hart and D.G. Stork (2001) Pattern Classification, New York: Wiley. Düntsch, I. and G. Gediga (1997) Statistical evaluation of rough set dependency analysis, International Journal of Human–Computer Studies, 46, 589– 604. Pawlak, Z. (1982) Rough sets, International Journal of Information and Computer Sciences, 11 (5), 341– 356. Pawlak, Z. (2002) Rough sets, decision algorithms and Bayes theorem, European Journal of Operational Research, 136, 181– 189. Slowinski, R. (1993) Rough set learning of preferential attitude in multi-criteria decision making, in Methodologies for Intelligent Systems, J. Komorowski and Z.W. Ras (eds), Lecture Notes in Artificial Intelligence Vol. 689, Berlin: Springer, 642– 651. Skowron, A. and C. Rauszer (1992) The discernibility matrices and functions in information systems, in Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory, R. Slowinski (ed.), Dordrecht: Kluwer Academic, 331– 362. Vinterbo, S. and A. Øhrn (2000) Minimal approximate hitting sets and rule templates, International Journal of Approximate Reasoning, 25 (2), 123– 143. Wong, S.K.M., W. Ziarko and R.L. Ye (1986) Comparison of rough-set and statistical methods in inductive learning, International Journal of Man–Machine Studies, 24, 53– 72. Ziarko, W. (1993) Variable precision rough set model, Journal of Computer and System Sciences, 46, 39– 59. Citing Literature Volume20, Issue5November 2003Pages 247-250 ReferencesRelatedInformation