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.
Author(s): | von Luxburg, U. |
Journal: | Foundations and Trends in Machine Learning |
Volume: | 2 |
Number (issue): | 3 |
Pages: | 235-274 |
Year: | 2010 |
Month: | July |
Day: | 0 |
Bibtex Type: | Article (article) |
DOI: | 10.1561/2200000008 |
Digital: | 0 |
Electronic Archiving: | grant_archive |
Language: | en |
Organization: | Max-Planck-Gesellschaft |
School: | Biologische Kybernetik |
Links: |
BibTex
@article{6333, title = {Clustering stability: an overview}, journal = {Foundations and Trends in Machine Learning}, 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 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.}, volume = {2}, number = {3}, pages = {235-274}, organization = {Max-Planck-Gesellschaft}, school = {Biologische Kybernetik}, month = jul, year = {2010}, slug = {6333}, author = {von Luxburg, U.}, month_numeric = {7} }