Label ranking: a new rule-based label ranking method

M. Gurrieri, X. Siebert, P. Fortemps, Salvatore Greco, R. Słowiński

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


    This work focuses on a particular application of preference ranking, wherein the problem is to learn a mapping from instances to rankings over a finite set of labels, i.e. label ranking. Our approach is based on a learning reduction technique and provides such a mapping in the form of logical rules: if [antecedent] then [consequent], where [antecedent] contains a set of conditions, usually connected by a logical conjunction operator (AND) while [consequent] consists in a ranking among labels. The approach presented in this paper mainly comprises five phases: preprocessing, rules generation, post-processing, classification and ranking generation.
    Original languageEnglish
    Title of host publicationAdvances on computational intelligence: 14th international conference on information processing and management of uncertainty in knowledge-based systems, proceedings, part 1
    EditorsSalvatore Greco, B. Bouchon-Meunier, G. Coletti, M. Fedrizzi, B. Matarazzo, R. Yager
    Place of PublicationBerlin
    Number of pages11
    ISBN (Print)9783642317088
    Publication statusPublished - 2012

    Publication series

    NameCommunications in computer and information science
    ISSN (Print)1865-0929


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