Performance of iterative clustering algorithms depends highly on the choice of cluster centers in each step. In this paper we propose an effective algorithm to compute new cluster centers for each iterative step for K-means clustering. This algorithm is based on the optimization formulation of the problem and a novel iterative method. The cluster centers computed using this methodology are found to be very close to the desired cluster centers, for iterative clustering algorithms. The experimental results using the proposed algorithm with a group of randomly constructed data sets are very promising.
Modified K-Means Clustering Algorithm
2008 Congress on Image and Signal Processing ; 4 ; 618-621
2008-05-01
198997 byte
Conference paper
Electronic Resource
English
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