• DocumentCode
    3540024
  • Title

    An improved PTAS approximation algorithm for k-means clustering problem

  • Author

    Shouqiang, Wang

  • Author_Institution
    Dept. of Inf. Eng., Shandong Jiaotong Univ., Jinan, China
  • fYear
    2012
  • fDate
    14-15 Aug. 2012
  • Firstpage
    90
  • Lastpage
    94
  • Abstract
    This paper presented an improved (1+ε)-randomized approximation algorithm proposed by Ostrovsky. The running time of the improved algorithm is O(2(O(kα2/ε))nd), where d,n denote the dimension and the number of the input points respectively, and α(<;1) represents the separated coefficient. The successful probability is (1/2(1-e(1/2ε)))k(1-O(√α)). Compared to the original algorithm, the improved algorithm runs more efficiency.
  • Keywords
    approximation theory; computational complexity; pattern clustering; randomised algorithms; O(2(O(kα2/ε))nd); improved (1+ε)-randomized approximation algorithm; improved PTAS approximation algorithm; k-means clustering problem; probability; Algorithm design and analysis; Approximation algorithms; Approximation methods; Bismuth; Clustering algorithms; Partitioning algorithms; Silicon; Algorith; Centroid; Clustering; Randomized Algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Uncertainty Reasoning and Knowledge Engineering (URKE), 2012 2nd International Conference on
  • Conference_Location
    Jalarta
  • Print_ISBN
    978-1-4673-1459-6
  • Type

    conf

  • DOI
    10.1109/URKE.2012.6319592
  • Filename
    6319592
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3540024