• DocumentCode
    2027808
  • Title

    Dynamic partitional clustering using evolution strategies

  • Author

    Lee, C.-Y. ; Antonsson, E.K.

  • Author_Institution
    Dept. of Mech. Eng., California Inst. of Technol., Pasadena, CA, USA
  • Volume
    4
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    2716
  • Abstract
    A novel evolution strategy implementing variable length genomes is developed to address the problem of dynamic partitional clustering. As opposed to static, dynamic partitional clustering does not require the a priori specification of the number of clusters. Results of the algorithm are presented and discussed for 2-D touching and non-touching cluster test cases
  • Keywords
    computational complexity; data analysis; data structures; 2-D touching; a priori specification; data analysis; data structures; dynamic partitional clustering; evolution strategies; variable length genomes; Automation; Bioinformatics; Clustering algorithms; Data analysis; Dynamic programming; Genomics; Humans; Mechanical engineering; Partitioning algorithms; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics Society, 2000. IECON 2000. 26th Annual Confjerence of the IEEE
  • Conference_Location
    Nagoya
  • Print_ISBN
    0-7803-6456-2
  • Type

    conf

  • DOI
    10.1109/IECON.2000.972427
  • Filename
    972427
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2027808