Paper Title:
A New Clustering Algorithm Partition K-Means
  Abstract

K-means is a classic algorithm of partition clustering, its speed is very fast, well, the clustering result is very sensitive to the initial cores. As a result, algorithm K-means does not always get the Global Optimization. To solve this problem, this paper proposes a new algorithm partition K-means, which selects the initial cores with a partition method and then cluster the data set with K-means. The experiment shows that the new algorithm gets better effect and better efficiency than the original algorithm K-means.

  Info
Periodical
Key Engineering Materials (Volumes 474-476)
Edited by
Garry Zhu
Pages
577-580
DOI
10.4028/www.scientific.net/KEM.474-476.577
Citation
M. Chen, C. J. Yin, Y. P. Xi, "A New Clustering Algorithm Partition K-Means", Key Engineering Materials, Vols. 474-476, pp. 577-580, 2011
Online since
April 2011
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$32.00
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