Convergence of alternative C-means clustering algorithms

Kiichi Urahama

    Research output: Contribution to journalLetterpeer-review

    3 Citations (Scopus)


    The alternative c-means algorithm has recently been presented by Wu and Yang [1] for robust clustering of data. In this letter, we analyze the convergence of this algorithm by transforming it into an equivalent form with the Legendre transform. It is shown that this algorithm converges to a local optimal solution from any starting point.

    Original languageEnglish
    Pages (from-to)752-754
    Number of pages3
    JournalIEICE Transactions on Information and Systems
    Issue number4
    Publication statusPublished - Apr 2003

    All Science Journal Classification (ASJC) codes

    • Information Systems
    • Computer Graphics and Computer-Aided Design
    • Software


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