Fuzzy rough sets and multiple-premise gradual decision rules

Salvatore Greco, M. Inuiguchi, R. Slowinski

Research output: Contribution to journalArticlepeer-review

Abstract

We propose a new fuzzy rough set approach which, differently from most 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 properties 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. The proposed approach to rule induction is also interesting from the viewpoint of philosophy supporting data mining and knowledge discovery, because it is concordant with the method of concomitant variations by John Stuart Mill. The decision rules are induced from lower and upper approximations defined for positive and negative relationships between credibility degrees of multiple premises, on one hand, and conclusion, on the other hand.
Original languageEnglish
Pages (from-to)179-211
Number of pages33
JournalInternational Journal of Approximate Reasoning
Volume41
Issue number2
DOIs
Publication statusPublished - Feb 2006

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