Rough sets and gradual decision rules

Salvatore Greco, M. Inuiguchi, R. Slowinski

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract

We propose a new fuzzy rough set approach which, differently from all known fuzzy set extensions of rough set theory, does not use any fuzzy logical connectives (t-norm, t-conorm, fuzzy implication). As there is no rationale for a particular choice of these connectives, avoiding this choice permits to reduce the part of arbitrary in the fuzzy rough approximation. Another advantage of the new approach is that it is based on the ordinal property of fuzzy membership degrees only. The concepts of fuzzy lower and upper approximations are thus proposed, creating a base for induction of fuzzy decision rules having syntax and semantics of gradual rules.
Original languageEnglish
Title of host publicationRough sets, fuzzy sets, data mining, and granular computing: proceedings of the 9th international conference
EditorsG. Wang, Q. Liu, Y. Yao, A. Skowron
Place of PublicationBerlin, Germany
PublisherSpringer
Pages156-164
Number of pages9
Volume2639
Edition2639
ISBN (Print)9783540140405
DOIs
Publication statusPublished - May 2003

Publication series

NameLecture notes in computer science
PublisherSpringer
Number2639

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