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  • 标题:A Dynamic Linkage Clustering using KD-Tree
  • 本地全文:下载
  • 作者:Shadi Abudalfa ; Mohammad Mikki
  • 期刊名称:The International Arab Journal of Information Technology
  • 印刷版ISSN:1683-3198
  • 出版年度:2013
  • 卷号:10
  • 期号:3
  • 出版社:Zarqa Private University
  • 摘要:Some clustering algorithms calculate connectivity of each data point to its cluster by depending on density reachability. These algorithms can find arbitrarily shaped clusters, but they require parameters that are mostly sensitive to clustering performance. We develop a new dynamic linkage clustering algorithm using kd-tree. The proposed algorithm does not require any parameters and does not have a worst-case bound on running time that exists in many similar algorithms in the literature. Experimental results are shown in this paper to demonstrate the effectiveness of the proposed algorithm. We compare the proposed algorithm with other famous similar algorithm that is shown in literature. We present the proposed algorithm and its performance in detail along with promising avenues of future research
  • 关键词:Data clustering; density-based clustering Algorithm; KD-tree; dynamic linkage clustering; DBSCAN
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