• DocumentCode
    668786
  • Title

    Improved FCM algorithm based on the initial clustering center selection

  • Author

    Qinrun Wen ; Lili Yu ; Yingjie Wang ; Weifeng Wang

  • Author_Institution
    Dept. of Software Eng., Shijiazhuang Inf. Eng. Vocational Coll., Shijiazhuang, China
  • fYear
    2013
  • fDate
    20-22 Nov. 2013
  • Firstpage
    351
  • Lastpage
    354
  • Abstract
    Fuzzy C-average algorithm (also known as the FCM algorithm) is a clustering algorithm based on partition. The idea of the algorithm is making is divided into clusters with the similarity between objects as large as possible, and the similarity between objects of different clusters as small as possible. As the algorithm is simple, easy to implement and computer clustering effect, etc., makes this algorithm in many fields has been widely applied. This paper focuses principles of FCM algorithm, the algorithm steps and its problems were described in detail and propose an improved algorithm.
  • Keywords
    data mining; fuzzy set theory; pattern clustering; FCM algorithm; computer clustering effect; data mining; fuzzy C-average algorithm; fuzzy cluster theory; initial clustering center selection; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Data mining; Linear programming; Partitioning algorithms; Software algorithms; Fuzzy C-average algorithm; Fuzzy Cluster Theory; clustering algorithm; initialization; weighted index;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Electronics, Communications and Networks (CECNet), 2013 3rd International Conference on
  • Conference_Location
    Xianning
  • Print_ISBN
    978-1-4799-2859-0
  • Type

    conf

  • DOI
    10.1109/CECNet.2013.6703344
  • Filename
    6703344