Bayesian decision theory for dominance-based rough set approach

Salvatore Greco, R. Slowinski, Y. Yao

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


    Dominance-based Rough Set Approach (DRSA) has been proposed to generalize classical rough set approach when consideration of monotonicity between degrees of membership to considered concepts has to be taken into account. This is typical for data describing various phenomena, e.g., "the larger the mass and the smaller the distance, the larger the gravity", or "the more a tomato is red, the more it is ripe". These monotonicity relationships are fundamental in rough set approach to multiple criteria decision analysis. In this paper, we propose a Bayesian decision procedure for DRSA. Our approach permits to take into account costs of misclassification in fixing parameters of the Variable Consistency DRSA (VC-DRSA), being a probabilistic model of 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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