Robust seed selection algorithm for k-means type algorithms

Details Robust seed selection algorithm for k-means type algorithms Robust seed selection algorithm for k-means type algorithms

2012-02-08

arxiv.org/abs/1202.1585v1

International Journal of Computer Science and Technology (IJCSIT), Vol 3, No 5, Oct 2011 pp 147-163

Computer Science

Computer Vision and Pattern Recognition

17 pages, 5 tables, 9figures

Scientific paper

10.5121/ijcsit.2011.3513

Selection of initial seeds greatly affects the quality of the clusters and in k-means type algorithms. Most of the seed selection methods result different results in different independent runs. We propose a single, optimal, outlier insensitive seed selection algorithm for k-means type algorithms as extension to k-means++. The experimental results on synthetic, real and on microarray data sets demonstrated that effectiveness of the new algorithm in producing the clustering results

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