• DocumentCode
    3423516
  • Title

    A New Selective Clustering Ensemble Algorithm

  • Author

    Liu Limin ; Fan Xiaoping

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Central South Univ., Changsha, China
  • fYear
    2012
  • fDate
    9-11 Sept. 2012
  • Firstpage
    45
  • Lastpage
    49
  • Abstract
    Selective clustering ensemble is usually based on the reference partition to select members of the ensemble. General method of generating reference partition is to use preliminary ensemble results, yet it cannot eliminate the influence of the inferior clustering partitions and the final clustering result is not satisfactory. In order to solve this problem, the paper proposes a new selective clustering ensemble algorithm. The new algorithm includes two points :(1) selecting the best reference partition based on clustering validity evaluation, (2)putting forward the new selection strategy and the method of member´s weight. The experimental results show that the new algorithm is effective and clustering accuracy could be significantly improved.
  • Keywords
    pattern clustering; clustering performance; clustering validity evaluation; member weight; preliminary ensemble; reference partition; reference partition selection strategy; selective clustering ensemble algorithm; Accuracy; Algorithm design and analysis; Clustering algorithms; Educational institutions; Iris; Partitioning algorithms; Pattern recognition; member´s weight; reference partition selection; selection strategy; selective clustering ensemble;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    e-Business Engineering (ICEBE), 2012 IEEE Ninth International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4673-2601-8
  • Type

    conf

  • DOI
    10.1109/ICEBE.2012.17
  • Filename
    6468216