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arXiv · 1602.08254

Theoretical Analysis of the $k$-Means Algorithm - A Survey

Johannes Blömer·Christiane Lammersen·Melanie Schmidt·Christian Sohler
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Abstract

The $k$-means algorithm is one of the most widely used clustering heuristics. Despite its simplicity, analyzing its running time and quality of approximation is surprisingly difficult and can lead to deep insights that can be used to improve the algorithm. In this paper we survey the recent results in this direction as well as several extension of the basic $k$-means method.

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Johannes Blömer, Christiane Lammersen, Melanie Schmidt, Christian Sohler. 2016-02-26. Theoretical Analysis of the $k$-Means Algorithm - A Survey. https://arxiv.org/abs/1602.08254

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