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Download Modified K-Means for Better Initial Cluster Centres
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Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology ISSN 2320–088X IJCSMC, Vol. 2, Issue. 7, July 2013, pg.219 – 223 RESEARCH ARTICLE Modified K-Means for Better Initial Cluster Centres Kalpana D. Joshi1, P.S. Nalwade2 1 2 Department of Computer Science, SGGSIE&T, Nanded, India Department of Computer Science, SGGSIE&T, Nanded, India 1 [email protected]; 2 [email protected] Abstract— The k-means clustering algorithm is most popularly used in data mining for real world applications. The efficiency and performance of the kmeans algorithm is greatly affected by initial cluster centers as different initial cluster centers often lead to different clustering. In this paper, we propose a modified k-means algorithm which has additional steps for selecting better cluster centers. We compute Min and Max distance for every cluster and find high density objects for selection of better k. Key Terms: - k-means; clustering; data mining; initial cluster centers; density objects Full Text: http://www.ijcsmc.com/docs/papers/July2013/V2I7201341.pdf © 2013, IJCSMC All Rights Reserved
