A New Clustering Algorithm Partition K-Means

Abstract:

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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 et al., "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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Price:

$35.00

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