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Selection of Initial Centroids for k-Means Algorithm?

Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.2, No. 7)

Publication Date:

Authors : ;

Page : 161-164

Keywords : Data mining; clustering; k-Means;

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Clustering is one of the important data mining techniques. k-Means [1] is one of the most important algorithm for Clustering. Traditional k-Means algorithm selects initial centroids randomly and in k-Means algorithm result of clustering highly depends on selection of initial centroids. k-Means algorithm is sensitive to initial centroids so proper selection of initial centroids is necessary. This paper introduces an efficient method to start the k-Means with good initial centroids. Good initial centroids are useful for better clustering.

Last modified: 2013-07-18 21:32:10