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  • 标题:Coupled Shortest Fuzzy C-Means Clustering Algorithm (CS-FCM) In Mixed Dataset
  • 本地全文:下载
  • 作者:M.Punithavalli ; A.S.Naveen Kumar
  • 期刊名称:International Journal of Innovative Research in Computer and Communication Engineering
  • 印刷版ISSN:2320-9798
  • 电子版ISSN:2320-9801
  • 出版年度:2013
  • 卷号:1
  • 期号:8
  • 出版社:S&S Publications
  • 摘要:Nowad ays Clustering in mixed dataset is a dynamic research topic in data mining concepts. Most of the clustering process is based on numerical attributes. That processes are not suitable for mixed dataset. The nature of mixed dataset is the combinat ion of numeric and categorical data type. Hence, the proposed technique required more efficiency to handle the mixed data set. This paper proposes a hybrid clustering technique CS-FCM that combines the concepts of hierarchical and fuzzy clustering for mixed dataset. Hence, in this paper, the proposed technique can handle the mixed data set easily. Moreover, it is coined for automated and effective clusters. This proposed technique is experimented with three type's data sets. Obviously, the experimental result shows that, they are inventive and have the capability to discover the number of clusters automatically from the mixed-dataset.
  • 关键词:Mixed Dataset; Hierarchical Clustering; Fuzzy Clustering; Fuzzy-C-Means clustering
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