Monotonic variable consistency rough set approaches

J. Blaszczynski, Salvatore Greco, R. Slowinski, M. Szelag

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

Abstract

We consider new definitions of Variable Consistency Rough Set Approaches that employ monotonic measures of membership to the approximated set. The monotonicity is understood with respect to the set of considered attributes. This kind of monotonicity is related to the monotonicity of the quality of approximation, considered among basic properties of rough sets. Measures that were employed by approaches proposed so far lack this property. New monotonic measures are considered in two contexts. In the first context, we define Variable Consistency Indiscernibility-based Rough Set Approach (VC-IRSA). In the second context, new measures are applied to Variable Consistency Dominance-based Rough Set Approaches (VC-DRSA). Properties of new definitions are investigated and compared to previously proposed Variable Precision Rough Set (VPRS) model, Rough Bayesian (RB) model and VC-DRSA.
Original languageEnglish
Title of host publicationRough sets and knowledge technology: proceedings of the second international conference
EditorsJ. Yao, P. Lingras, W. Wu, M. Szczuka, N. Cercone, D. Slezak
Place of PublicationBerlin
PublisherSpringer
Pages126-133
Number of pages8
Volume4481
Edition4481
ISBN (Print)9783540724575
DOIs
Publication statusPublished - 2007

Publication series

NameLecture notes in computer science
PublisherSpringer
Number4481

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