计算机工程与应用Issue(22)：149-153,5.DOI:10.3778/j.issn.1002-8331.1212-0253
改进的最小生成树自适应分层聚类算法
Improved adaptive hierarchical clustering algorithm based on minimum spanning tree
摘要
Abstract
Classical clustering algorithm based on the minimum spanning tree often needs to know the number of clusters beforehand and use static global threshold to cluster, which leads to the performance of the algorithm low and the compu-tation complex for the uneven distributed data. An improved adaptive hierarchical clustering algorithm based on minimum spanning tree is proposed, which automatically generates different thresholds for every cluster to adapt for the uneven dis-tributed data according to the nearest neighbor relationship and adaptively determines the number of clusters. Experiments demonstrate that this algorithm has good performance, especially could cluster effectively for the uneven distributed data.关键词
最近邻/自适应聚类/最小生成树/聚类分析Key words
nearest neighbor/adaptive clustering/minimum spanning tree/clustering analysis分类
信息技术与安全科学引用本文复制引用
徐晨凯,高茂庭..改进的最小生成树自适应分层聚类算法[J].计算机工程与应用,2014,(22):149-153,5.基金项目
上海市科委科技创新项目（No.12595810200）；上海海事大学科研项目。 （）
