摘要
k-means算法是经常使用的一种聚类算法,但是易受聚类个数k的影响,其性能主要取决于k值优化,因此对近年来k-means算法的研究现状与进展进行总结。对较有代表性的k值优化的k-means算法,从思想、关键技术等方面进行分析概括,并选用著名数据集对一些典型算法进行了测试,主要从同一个数据集、不同的k值优化情况进行对比分析.上述工作将为聚类分析和数据挖掘的研究提供有益的参考.
k-means Clustering Algorithm is widely used and is sensitive to k. The performance of the k-means Clustering Algorithm primary depends on the optimization of k. In this paper, the progresses on k-means algorithm were summarized. Firstly, some representative k-means algorithms about the optimization of k were outlined. Secondly, several known data sets were selected to test some typical k-means algorithms. The work will be valuable for data clustering and data mining.
出处
《海南大学学报（自然科学版）》
CAS
2009年第4期386-389,共4页
Natural Science Journal of Hainan University
基金
黑龙江省自然科学基金项目(F200603)
