• DocumentCode
    2004312
  • Title

    Independence based clustering

  • Author

    Nishigaki, Takahiro ; Onoda, Takashi

  • Author_Institution
    Dept. of Comput. Intell. & Syst. Sci., Tokyo Inst. of Technol., Yokohama, Japan
  • fYear
    2012
  • fDate
    20-24 Nov. 2012
  • Firstpage
    386
  • Lastpage
    390
  • Abstract
    Existing clustering methods focus on the similarity of data within the cluster. Therefore, distance and independence between clusters were not taken into account. However, users expect that the data within a cluster are similar, and data in different clusters are well separated or independent from each other. In this paper, we propose a clustering method where data within a cluster are similar, and data between clusters are highly independent. We show the results of experiments using benchmark data. And we carried out a survey with high school students.
  • Keywords
    pattern clustering; benchmark data; data similarity; high school students; independence based clustering; clustering; independent component analysis; k-means;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on
  • Conference_Location
    Kobe
  • Print_ISBN
    978-1-4673-2742-8
  • Type

    conf

  • DOI
    10.1109/SCIS-ISIS.2012.6505162
  • Filename
    6505162