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    Please use this identifier to cite or link to this item: http://ir.lib.ksu.edu.tw/handle/987654321/5704

    Title: An analysis of partition index maximization algorithm
    Authors: Kuo-Lung Wu (吳國龍)
    Date: 2009-08-20
    Issue Date: 2009-11-20 00:32:00 (UTC+8)
    Abstract: In the traditional fuzzy c-means clustering
    algorithm, nearly no data points have a membership value
    one. Ozdemir  and Akarum proposed a partition index
    maximization (PIM) algorithm which allows the data
    points can whole belonging to one cluster. This
    modification can form a core for each cluster and data
    points inside the core will have membership value {0,1}. In
    this paper, we will discuss the parameter selection
    problems and robust properties of the PIM algorithm.
    Relation: K.L. Wu, An analysis of partition index maximization algorithm, 2009 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE, ICC Jeju, Jeju Island, Korea, August 20~24, 2009, pp. 1785-1790.
    Appears in Collections:[資訊管理系所] 會議論文

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