Clustering Stability: An Overview

Details Clustering Stability: An Overview Clustering Stability: An Overview

2010-07-07

arxiv.org/abs/1007.1075v1

Foundations and Trends in Machine Learning, Vol. 2, No. 3, p. 235-274, 2010

Statistics

Machine Learning

Scientific paper

10.1561/2200000008

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 paper 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.

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