An Improved approach for K-Means using Parallel Processing

被引：1
作者：
Swamy, Prateek [1 ]
Raghuwanshi, M. M. [2 ]
Gholghate, Ashish [1 ]
机构：
[1] Rajiv Gandhi Coll Engn & Res, Dept Comp Sci & Engn, Nagpur, Maharashtra, India
[2] Yeshwantrao Chavan Coll Engn, Dept Comp Technol, Nagpur, Maharashtra, India
来源：
1ST INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION ICCUBEA 2015 | 2015年
关键词：
Serial execution; large dataset; Parallel processing; K-Means; execution time; accuracy; initial cluster centers;
D O I：
10.1109/ICCUBEA.2015.75
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：358 / 361
页数：4
相关论文
共 17 条
  • [1] Ashtari N, 2014, IEEE T EMERGING TOPI
  • [2] Bhupal Naik DS., 2013, IEEE INT C COMP INT
  • [3] Dunham Margaret H., 2006, PEARSON ED
  • [4] Fahim AM., 2006, J ZHEJIANG UNIV-SC A, V7, P1626, DOI [DOI 10.1631/JZUS.2006.A1626, https://doi.org/10.1631/jzus.2006.A1626, 10.1631/jzus.2006.A1626]
  • [5] FANG Yuan, 2004, 3 INT C MACH LAM CYB
  • [6] Fayyad U, 1996, AI MAG, V17, P37
  • [7] Goil S., 1999, MAFIA EFFICIENT SCAL
  • [8] In search of optimal centroids on data clustering using a binary search algorithm
    Hatamlou, Abdolreza
    [J]. PATTERN RECOGNITION LETTERS, 2012, 33 (13) : 1756 - 1760
  • [9] Data clustering: A review
    Jain, AK
    Murty, MN
    Flynn, PJ
    [J]. ACM COMPUTING SURVEYS, 1999, 31 (03) : 264 - 323
  • [10] Data clustering: 50 years beyond K-means
    Jain, Anil K.
    [J]. PATTERN RECOGNITION LETTERS, 2010, 31 (08) : 651 - 666
12