Clustering Stability: An Overview
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.
Cite
Text
von Luxburg. "Clustering Stability: An Overview." Foundations and Trends in Machine Learning, 2009. doi:10.1561/2200000008Markdown
[von Luxburg. "Clustering Stability: An Overview." Foundations and Trends in Machine Learning, 2009.](https://mlanthology.org/ftml/2009/vonluxburg2009ftml-clustering/) doi:10.1561/2200000008BibTeX
@article{vonluxburg2009ftml-clustering,
title = {{Clustering Stability: An Overview}},
author = {von Luxburg, Ulrike},
journal = {Foundations and Trends in Machine Learning},
year = {2009},
pages = {235-274},
doi = {10.1561/2200000008},
volume = {2},
url = {https://mlanthology.org/ftml/2009/vonluxburg2009ftml-clustering/}
}