• DocumentCode
    2200233
  • Title

    An Improved RPCL Algorithm for Determining Clustering Number Automatically

  • Author

    Yang, Jun ; Jin, Lianwen

  • Author_Institution
    Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou
  • fYear
    2006
  • fDate
    14-17 Nov. 2006
  • Firstpage
    1
  • Lastpage
    3
  • Abstract
    Conventional k-means needs to know the exact cluster number before performing data clustering. Otherwise, it may lead to a poor clustering performance. The rival penalized competitive learning algorithm (RPCL) can automatically select the correct cluster number, but it is sensitive to the learning rate and the de-learning rate especially the de leaning rate. This paper presents an improved RPCL algorithm, which is based on the evaluation of competition ability between the winner and the rival, the improved RPCL algorithm could determining clustering number without the selecting of de learning rate. Our experiments have shown that this improved algorithm can find out the correct clustering number more quickly and convenient than RPCL algorithm
  • Keywords
    unsupervised learning; RPCL algorithm; clustering number determination; rival penalized competitive learning algorithm; Algorithm design and analysis; Clustering algorithms; Data engineering; Data mining; Image analysis; Image processing; Pattern analysis; Pattern recognition; Publishing; Signal analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    TENCON 2006. 2006 IEEE Region 10 Conference
  • Conference_Location
    Hong Kong
  • Print_ISBN
    1-4244-0548-3
  • Electronic_ISBN
    1-4244-0549-1
  • Type

    conf

  • DOI
    10.1109/TENCON.2006.344112
  • Filename
    4142227