AN AVERAGE-BASED APPROACH FOR INITIAL CENTROID SELECTION IN K- MEANS ALGORITHM

A. Shafiq; M. Rehman; M. Anjum

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AN AVERAGE-BASED APPROACH FOR INITIAL CENTROID SELECTION IN K- MEANS ALGORITHM

Author(s)

A. Shafiq Department of Computer Science, Lahore College for Women University,Lahore,Pakistan

M. Rehman Department of Computer Science, Lahore College for Women University,Lahore,Pakistan

M. Anjum Department of Computer Science, Lahore College for Women University,Lahore,Pakistan

Abstract

The underlying research work was focused on one of the standard k-means issue of initial centroid selection. An average based approach was used for avoiding random cluster initialization. The experiments of this study showed that the results obtained with proposed method were better and consistent. It was concluded that the proposed method had less classification error, reduced total number of iterations and took less execution time than random initialization method.

Publication Details

Page(s) 441-444

DOI DOI not available

Published Journal: Pakistan Journal of Science, Volume: 68, Issue: 4, Year: 2016

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Keywords

Initial centroids, Data clustering, Partitioned-based clustering algorithms