• DocumentCode
    1708608
  • Title

    Research and improvement of clustering algorithm in data mining

  • Author

    Jingbiao, Ren ; Shaohong, Yin

  • Author_Institution
    Tianjin Polytech. Univ., Tianjin, China
  • Volume
    1
  • fYear
    2010
  • Abstract
    This paper is a cluster analysis algorithm research carried out based on the existing data mining, which focuses on the current popular and commonly used K-means algorithm, and presents an improved K-harmonic means clustering algorithm through using a new distance measure. Through the regulation of distance metric parameters can achieve better clustering effects than the traditional K-harmonic means, and has an advantage both in run time and number of iterations.
  • Keywords
    data mining; pattern clustering; K-harmonic means clustering algorithm; cluster analysis algorithm; data mining; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Data mining; Heuristic algorithms; Partitioning algorithms; Signal processing algorithms; K-means algorithm; clustering analysis; data mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Systems (ICSPS), 2010 2nd International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-1-4244-6892-8
  • Electronic_ISBN
    978-1-4244-6893-5
  • Type

    conf

  • DOI
    10.1109/ICSPS.2010.5555239
  • Filename
    5555239