计算机科学 ›› 2016, Vol. 43 ›› Issue (Z6): 454-456.doi: 10.11896/j.issn.1002-137X.2016.6A.107

• 数据挖掘 • 上一篇    下一篇

一种基于聚类中心的快速聚类算法

周鹿扬,程文杰,徐建鹏,徐祥   

  1. 安徽省农村综合经济信息中心 合肥230001,安徽省农村综合经济信息中心 合肥230001;安徽省农业气象中心 合肥230001,安徽省农村综合经济信息中心 合肥230001;安徽省农业气象中心 合肥230001,安徽省农村综合经济信息中心 合肥230001
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家科技计划项目(2014BAD10B05)资助

Fast Clustering Algorithm Based on Cluster-centers

ZHOU Lu-yang, CHENG Wen-jie, XU Jian-peng and XU Xiang   

  • Online:2018-11-14 Published:2018-11-14

摘要: 针对k-means算法采用单一的聚类中心描述一个类簇,一般不能有效适用于任意形状簇的缺陷,在研究k-means算法以及初始聚类中心优化算法的基础上,考虑将数据集中较大或延伸状的簇分割成若干球状簇,而后合并这些小簇。该算法首先选取一组分布于高密度区域的聚类中心,将聚类中心周围的对象划分到离其最近的聚类中心形成子簇,再根据子簇之间的连通性完成子簇合并。实验证明,该算法能有效适应任意形状簇,并保持了k-means算法简单的优点。

关键词: 聚类算法,聚类中心,簇合并,快速

Abstract: To deal with the problem that classical k-means algorithm inefficiently adapt to clustering for all kinds of clusters,in this paper an algorithm which is improved on k-means algorithm using optimization cluster-center was proposed.It divides large or extended-shaped cluster into a number of globular clusters,and then merges these small clusters.Firstly,a group of cluster centers located in the high-density region are selected,and the object around the cluster center is divided to its nearest cluster center forming the sub-cluster.Then the merger is completed in accordance with sub-cluster connectivity between sub-clusters.Experimental results show that the algorithm can adapt to irregular shape cluster and is simple.

Key words: Clustering algorithm,Cluster-center,Cluster consolidation,Fast

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