• DocumentCode
    458847
  • Title

    Finding Groups in Data: Cluster Analysis with Ants

  • Author

    Boryczka, Urszula

  • Author_Institution
    Inst. of Comput. Sci., Silesia Univ., Sosnowiec
  • Volume
    1
  • fYear
    2006
  • fDate
    16-18 Oct. 2006
  • Firstpage
    404
  • Lastpage
    409
  • Abstract
    We present in this paper a modification of Lumer and Faieta´s algorithm for data clustering. This algorithm discovers automatically clusters in numerical data without prior knowledge of possible number of clusters. We have applied this algorithm on standard databases and we get very good results compared to the AntClass, k-means and ISODATA algorithms for IRIS dataset
  • Keywords
    artificial life; optimisation; pattern clustering; ant-based clustering; data clustering; Algorithm design and analysis; Clustering algorithms; Computer science; Data analysis; Data mining; Databases; Iris; Partitioning algorithms; Simulated annealing; Sorting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    0-7695-2528-8
  • Type

    conf

  • DOI
    10.1109/ISDA.2006.151
  • Filename
    4021473
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=458847