Abstract
A popular method for selecting the number of clusters is based on stability arguments: one chooses the number of clusters such that the corresponding clustering results are "most stable". In recent years, a series of papers has analyzed the behavior of this method from a theoretical point of view. However, the results are very technical and difficult to interpret for non-experts. In this monograph we give a high-level overview about the existing literature on clustering stability. In addition to presenting the results in a slightly informal but accessible way, we relate them to each other and discuss their different implications. © 2010 U. von Luxburg.
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CITATION STYLE
Von Luxburg, U. (2009). Clustering stability: An overview. Foundations and Trends in Machine Learning, 2(3), 129–168. https://doi.org/10.1561/2200000008
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