期刊論文

學年 89
學期 2
出版(發表)日期 2001-02-01
作品名稱 A novel algorithm for data clustering
作品名稱(其他語言)
著者 翁慶昌; Wong, Ching-chang; Chen, Chia-chong; Su, Mu-chun
單位 淡江大學電機工程學系
出版者 Elsevier
著錄名稱、卷期、頁數 Pattern Recognition 34(2), pp.425-442
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.
關鍵字 Data clustering;Unsupervised classification
語言 en
ISSN 0031-3203
期刊性質 國外
收錄於
產學合作
通訊作者
審稿制度
國別 NLD
公開徵稿
出版型式 ,紙本
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