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    Please use this identifier to cite or link to this item: http://ir.cnu.edu.tw/handle/310902800/26974


    標題: A time-efficient pattern reduction algorithm for k-means clustering
    作者: Chiang, Ming-Chao
    Tsai, Chun-Wei
    Yang, Chu-Sing
    貢獻者: 應用空間資訊系
    關鍵字: Data clustering
    k-means
    Pattern reduction
    日期: 2011-02
    上傳時間: 2013-10-14 14:57:44 (UTC+8)
    出版者: Elsevier
    摘要: This paper presents an efficient algorithm, called pattern reduction (PR), for reducing the computation time of k-means and k-means-based clustering algorithms. The proposed algorithm works by compressing and removing at each iteration patterns that are unlikely to change their membership thereafter. Not only is the proposed algorithm simple and easy to implement, but it can also be applied to many other iterative clustering algorithms such as kernel-based and population-based clustering algorithms. Our experiments—from 2 to 1000 dimensions and 150 to 10,000,000 patterns—indicate that with a small loss of quality, the proposed algorithm can significantly reduce the computation time of all state-of-the-art clustering algorithms evaluated in this paper, especially for large and high-dimensional data sets.
    關聯: Information Sciences , 181(4), pp.716-731
    Appears in Collections:[應用空間資訊系(所)] 期刊論文

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