• DocumentCode
    3111759
  • Title

    An Improved Approach for k-Means Using Parallel Processing

  • Author

    Swamy, Prateek ; Raghuwanshi, M.M. ; Gholghate, Ashish

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Rajiv Gandhi Coll. of Eng. & Res., Nagpur, India
  • fYear
    2015
  • fDate
    26-27 Feb. 2015
  • Firstpage
    358
  • Lastpage
    361
  • Abstract
    Serial execution of K-means algorithm on large dataset takes more execution time and does not give accurate results. Parallel processing is one of the ways to improve the performance of K-Means algorithm. But the execution time and accuracy is largely dependent on selection of initial cluster centers. In this paper, parallel processing of K-Means is proposed using an initialization method to originate initial cluster centers, which not only reduces the execution time but also gives accurate results.
  • Keywords
    parallel processing; pattern classification; pattern clustering; execution time; initial cluster centers; initialization method; k-means algorithm; parallel processing; Accuracy; Algorithm design and analysis; Clustering algorithms; Convergence; Machine learning algorithms; Mathematical model; Parallel processing; K-Means; Parallel processing; Serial execution; accuracy; execution time; initial cluster centers; large dataset;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing Communication Control and Automation (ICCUBEA), 2015 International Conference on
  • Conference_Location
    Pune
  • Type

    conf

  • DOI
    10.1109/ICCUBEA.2015.75
  • Filename
    7155867
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3111759