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


    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
    Number of pages8
    ISBN (Print)9783540724575
    Publication statusPublished - 2007

    Publication series

    NameLecture Notes in Computer Science


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