A Clustering Method Based on K-Means Algorithm

In this paper we combine the largest minimum distance algorithm and the traditional K-Means algorithm to propose an improved K-Means clustering algorithm. This improved algorithm can make up the shortcomings for the traditional K-Means algorithm to determine the initial focal point. The improved K-M...

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Bibliographic Details
Published inPhysics procedia Vol. 25; pp. 1104 - 1109
Main Authors Li, Youguo, Wu, Haiyan
Format Journal Article
LanguageEnglish
Published Elsevier B.V 2012
Subjects
cluster analysis
distance algorithm
K-Means algorithm
samples of pattern
distance algorithm
cluster analysis
K-Means algorithm
samples of pattern
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Summary:In this paper we combine the largest minimum distance algorithm and the traditional K-Means algorithm to propose an improved K-Means clustering algorithm. This improved algorithm can make up the shortcomings for the traditional K-Means algorithm to determine the initial focal point. The improved K-Means algorithm effectively solved two disadvantages of the traditional algorithm, the first one is greater dependence to choice the initial focal point, and another one is easy to be trapped in local minimum[1,2].
ISSN:1875-3892
1875-3892
DOI:10.1016/j.phpro.2012.03.206