• DocumentCode
    3456946
  • Title

    Fuzzy C-Means Clustering Algorithm Based on Incomplete Data

  • Author

    Jia, Zhiping ; Yu, Zhiqiang ; Zhang, Chenghui

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Univ. of Shandong, Jinan
  • fYear
    2006
  • fDate
    20-23 Aug. 2006
  • Firstpage
    600
  • Lastpage
    604
  • Abstract
    In order to solve the problem that the traditional fuzzy c-means(FCM) clustering algorithm can not directly act on incomplete data, a modified algorithm IDFCM(Incomplete Data FCM) based on the FCM algorithm is proposed. The IDFCM algorithm takes the percentage of incomplete data in datasets and its effect on clustering analysis into consideration. Finally, the experimental clustering results of IRIS data and mobile distributed inspected data of the ocean are given, which can clearly prove that the IDFCM algorithm is very efficient for clustering incomplete data.
  • Keywords
    fuzzy set theory; pattern clustering; IRIS data; fuzzy c-means clustering algorithm; incomplete data; mobile distributed data; Algorithm design and analysis; Clustering algorithms; Computer science; Data engineering; Fuzzy control; Fuzzy sets; Iris; Oceans; Partitioning algorithms; Prototypes; FCM algorithm; IDFCM algorithm; fuzzy clustering; incomplete datum;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Acquisition, 2006 IEEE International Conference on
  • Conference_Location
    Shandong
  • Print_ISBN
    1-4244-0528-9
  • Electronic_ISBN
    1-4244-0529-7
  • Type

    conf

  • DOI
    10.1109/ICIA.2006.305793
  • Filename
    4097726