J4 ›› 2010, Vol. 32 ›› Issue (10): 105-107.doi: 10.3969/j.issn.1007130X.2010.
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WANG Saifang,DAI Fang,WANG Wanbin,ZHANG Xiaoyu
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Abstract:
Traditional Kmeans clustering algorithms are sensitive to the selection of initial clustering centers and isolated points. Considering these problems, a new method based on the density of points is presented in this paper. First of all, we select initial clustering centers through the proposed method. Then, we apply a Kmeans clustering algorithm to cluster the data, and process the isolated points especially. The experimental results demonstrate that the proposed method can get better clustering results.
Key words: clustering;Kmeans clustering algorithm;density of points
WANG Saifang,DAI Fang,WANG Wanbin,ZHANG Xiaoyu. A KMeans Algorithm Based onthe Optimal Initial Clustering Center[J]. J4, 2010, 32(10): 105-107.
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URL: http://joces.nudt.edu.cn/EN/10.3969/j.issn.1007130X.2010.
http://joces.nudt.edu.cn/EN/Y2010/V32/I10/105