A New Clustering Algorithm Partition K-Means

Min Chen; Chan Juan Yin; Yu Ping Xi

doi:10.4028/www.scientific.net/KEM.474-476.577

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HomeKey Engineering MaterialsKey Engineering Materials Vols. 474-476A New Clustering Algorithm Partition K-Means

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.

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Periodical:

Key Engineering Materials (Volumes 474-476)

Pages:

577-580

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.474-476.577

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Online since:

April 2011

Authors:

Min Chen, Chan Juan Yin, Yu Ping Xi

Keywords:

Algorithm K-Means, Initial Cores, Partition K-Means

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