Constrained Intelligent K-Means: Improving Results with Limited Previous Knowledge

Renato Cordeiro de Amorim

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    13 Citations (Scopus)
    162 Downloads (Pure)

    Abstract

    It is here presented a new method for clustering that uses very limited amount of labeled data, employees two pairwise rules, namely must link and cannot link and a single wise one, cannot cluster. It is demonstrated that the incorporation of these rules in the intelligent k-means algorithm may increase the accuracy of results, this is proven with experiments where the real number of clusters in the data is unknown to the method
    Original languageEnglish
    Title of host publicationProcs of the Second Int Conf on Advanced Engineering Computing and Applications in Sciences, 2008
    Subtitle of host publicationADVCOMP'08
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)
    Pages176-180
    Number of pages5
    ISBN (Electronic)978-0-7695-3369-8
    ISBN (Print)978-0-7695-3369-8
    DOIs
    Publication statusPublished - 2008
    EventSecond Int Conf on Advanced Engineering Computing and Applications in Sciences, 2008. ADVCOMP'08 - Valencia, Spain
    Duration: 29 Sept 20084 Oct 2008

    Conference

    ConferenceSecond Int Conf on Advanced Engineering Computing and Applications in Sciences, 2008. ADVCOMP'08
    Country/TerritorySpain
    CityValencia
    Period29/09/084/10/08

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