Analysis of the k-means algorithm in the case of data points occurring on the border of two or more clusters
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摘要
In this paper, the well-known k-means algorithm for searching for a locally optimal partition of the set A⊂Rn is analyzed in the case if some data points occur on the border of two or more clusters. For this special case, a useful strategy by implementation of the k-means algorithm is proposed.
论文关键词：k-Means,Clustering,Data mining,Least square distance-like function,Locally optimal partition,Cluster border
论文评审过程：Received 24 August 2013, Revised 4 November 2013, Accepted 9 November 2013, Available online 20 November 2013.
论文官网地址：https://doi.org/10.1016/j.knosys.2013.11.010
