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    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/46125

    題名: A novel algorithm for data clustering
    作者: 翁慶昌;Wong, Ching-chang;Chen, Chia-chong;Su, Mu-chun
    貢獻者: 淡江大學電機工程學系
    關鍵詞: Data clustering;Unsupervised classification
    日期: 2001-02
    上傳時間: 2010-03-26 21:00:15 (UTC+8)
    出版者: Elsevier
    摘要: An efficient clustering algorithm is proposed in an unsupervised manner to cluster the given data set. This method is based on regulating a similarity measure and replacing movable vectors so that the appropriate clusters are determined by a performance for the classification validity. The proposed clustering algorithm needs not to predetermine the number of clusters, to choose the appropriate cluster centers in the initial step, and to choose a suitable similarity measure according to the shapes of the data. The location of the cluster centers can be efficiently determined and the data can be correctly classified by the proposed method. Several examples are considered to illustrate the effectiveness of the proposed method.
    關聯: Pattern Recognition 34(2), pp.425-442
    DOI: 10.1016/S0031-3203(00)00002-9
    顯示於類別:[電機工程學系暨研究所] 期刊論文


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