L'algorithme OKM pour la classification recouvrante: la détermination du nombre de classes

  • Clément Guiot

    Student thesis: Master typesMaster in Mathematics

    Abstract

    The goal of this report is to adapt two methods for estimating the number optimal of clusters to the overlapping clustering and to attach them to the OKM algorithm. These two methods are the method gamma and a modified version of the Gap Statistic. In this report, we study the performance of this algorithm on a real data set and we attach to it the two methods for estimating the number optimal of clusters. We apply then these methods on different kinds of artificial or real data and we analyze the results.
    Date of Award5 Sept 2011
    Original languageFrench
    SupervisorAndre Hardy (Supervisor), Renaud Lambiotte (Jury), Marcel Remon (Jury) & Anne Lemaitre (Jury)

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