• DocumentCode
    2313116
  • Title

    Genetic Algorithm Based Clustering: A Survey

  • Author

    Sheikh, Rahila H. ; Raghuwanshi, M.M. ; Jaiswal, Anil N.

  • Author_Institution
    RCERT, Chandrapur
  • fYear
    2008
  • fDate
    16-18 July 2008
  • Firstpage
    314
  • Lastpage
    319
  • Abstract
    This survey gives state-of-the-art of genetic algorithm (GA) based clustering techniques. Clustering is a fundamental and widely applied method in understanding and exploring a data set. Interest in clustering has increased recently due to the emergence of several new areas of applications including data mining, bioinformatics, web use data analysis, image analysis etc. To enhance the performance of clustering algorithms, Genetic Algorithms (GAs) is applied to the clustering algorithm. GAs are the best-known evolutionary techniques. The capability of GAs is applied to evolve the proper number of clusters and to provide appropriate clustering. This paper present some existing GA based clustering algorithms and their application to different problems and domains.
  • Keywords
    data mining; genetic algorithms; pattern classification; pattern clustering; unsupervised learning; data clustering algorithm; data mining; evolutionary technique; genetic algorithm; unsupervised pattern classification; Bioinformatics; Biological cells; Clustering algorithms; Data analysis; Data mining; Genetic algorithms; Genetic engineering; Genetic mutations; Image analysis; Partitioning algorithms; GA based clustering; Genetic algorithm; clustering algorithms; pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Trends in Engineering and Technology, 2008. ICETET '08. First International Conference on
  • Conference_Location
    Nagpur, Maharashtra
  • Print_ISBN
    978-0-7695-3267-7
  • Electronic_ISBN
    978-0-7695-3267-7
  • Type

    conf

  • DOI
    10.1109/ICETET.2008.48
  • Filename
    4579917