Rough set approach to KDD (extended abstract)

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Abstract

This tutorial is a survey on rough set theory and some of its applications in Knowledge Discovery from Databases (KDD). It will also cover the practice guide to analysis of different real life problems using rough set methods as well as the presentation of Rough Set Exploration System (RSES) what can be treated as a preliminary material for the main conference and associated workshops. Rough Set theory was introduced by Zdzisław Pawlak in the early 80's and has currently reached a level of high visibility and maturity [3,2,4,5,6] Originally, rough sets, whose main philosophy is based simply on indiscernibility and discernibility of objects, were presented as an approach to concept approximation under uncertainty. This brilliantly simple idea has been successively expanded in the last twenty years. Many effective methods for data analysis have been developed on the basis of rough set theory. © 2008 Springer-Verlag Berlin Heidelberg.

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APA

Nguyen, H. S., & Skowron, A. (2008). Rough set approach to KDD (extended abstract). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5009 LNAI, pp. 19–20). https://doi.org/10.1007/978-3-540-79721-0_4

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