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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/987654321/52774

    題名: On the Approach of Automatic Adjustments for Gaussian-Mixture Clustering
    作者: 郭經華;Kuo, Chin-hwa;Chou, Tzu-chuan;Chen, Meng-chang
    貢獻者: 淡江大學資訊工程學系
    關鍵詞: Parameter estimation of gaussian mixture;EM algorithm;Clustering algorithm;Local optima
    日期: 2006-06-01
    上傳時間: 2010-12-01 10:29:56 (UTC+8)
    出版者: 臺北縣:淡江大學
    摘要: In this paper, we discuss the dual-problem of adjusting the mixture number and avoiding local optima in the estimation of a Gaussian mixture. This estimation is widely used in unsupervised-classification applications; however, its results are serially sensitive to the initial setting, which is difficult to optimize. It is also difficult to automatically designate the mixture number in advance. In much of the literature, these two issues are discussed separately, meaning that one is considered at the expense of the other. To overcome this problem, we present some strategies that automatically and simultaneously adjust the mixture number and escape from local optima. The evaluation results are very encouraging and show that the proposed strategies are effective.
    關聯: 淡江理工學刊=Tamkang journal of science and engineering 9(2),頁155-166
    DOI: 10.6180/jase.2006.9.2.10
    顯示於類別:[資訊工程學系暨研究所] 期刊論文


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