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A Computational Comparison of the p-Median Clustering and k-Means

Anton V. Ushakov, Igor L. Vasilyev, Tatyana V. Gruzdev


In this paper the p-median clustering approach, often referred to as minimum sum-of-stars, is considered. An intensive computational experiment on test clustering problems is reported, showing that the approach under consideration totally outperforms the popular kmeans and its modification k-means++. This assumption is made by the comparison of obtained clustering solutions using five popular quality measures.


p-median, k-means, k-means++, sum-of-stars, data clustering, Lagrangean heuristic, clustering quality, entropy, purity, f-measure.

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