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一种改进的K-means算法

Chun-yan HAN

JOURNAL OF NEIJIANG NORMAL UNIVERSITY（2009）

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Abstract
传统的K-means算法对初始聚类中心敏感,聚类的结果随不同的初始输入而波动.为了消除这种敏感性,提出了一种改进的K-means算法,改善聚类算法中选取初值的依赖性,提高聚类结果的稳定性.仿真实验结果表明:改进后的K-means算法优于原始算法.
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Key words
K-means,Clustering Algorithms
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