Alternative normalization schemas for bayesian confirmation measures

Salvatore Greco, R. Slowinski, I. Szczech

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


    Analysis of rule interestingness measures with respect to their properties is an important research area helping to identify groups of measures that are truly meaningful. In this article, we analyze property Ex 1, of preservation of extremes, in a group of confirmation measures. We consider normalization as a mean to transform them so that they would obtain property Ex 1 and we introduce three alternative approaches to the problem: an approach inspired by Nicod, Bayesian, and likelihoodist approach. We analyze the results of the normalizations of seven measures with respect to property Ex 1 and show which approaches lead to the desirable results. Moreover, we extend the group of ordinally non-equivalent measures possessing valuable property Ex 1.
    Original languageEnglish
    Title of host publicationComputational intelligence for knowledge-based systems design: 13th international conference on information processing and management of uncertainty
    EditorsE. Hullermeier, R. Kruse, F. Hoffmann
    Place of PublicationBerlin
    Number of pages10
    ISBN (Print)9783642140488
    Publication statusPublished - Jul 2010

    Publication series

    NameLecture notes in computer science
    ISSN (Print)0302-9743


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