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  • 标题:A Novel Algorithm for Dual Similarity Clusters Using Minimum Spanning Tree
  • 本地全文:下载
  • 作者:S.john Peter, S.P.victor
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2010
  • 卷号:14
  • 期号:01
  • 出版社:Journal of Theoretical and Applied
  • 摘要:

    The minimum spanning tree clustering algorithm is capable of detecting clusters with irregular boundaries. In this paper we propose minimum spanning trees based clustering algorithm. The algorithm produces k clusters with center and it also creates a dendrogram for the k clusters. The algorithm works in two phases. The first phase of the algorithm produces subtrees. The second phase converts the subtrees into dendrogram. The key feature of the algorithm is it uses both divisive and agglomerative approaches to find Dual similarity clusters.

  • 关键词:Euclidean Minimum Spanning Tree; Clustering; Eccentricity; Center; Hierarchical Clustering; Dendrogram ; Subtree
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