Batool, F;
Hennig, C;
(2021)
Clustering with the Average Silhouette Width.
Computational Statistics & Data Analysis
, 158
, Article 107190. 10.1016/j.csda.2021.107190.
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Abstract
The Average Silhouette Width (ASW) is a popular cluster validation index to estimate the number of clusters. The question whether it also is suitable as a general objective function to be optimized for finding a clustering is addressed. Two algorithms (the standard version OSil and a fast version FOSil) are proposed, and they are compared with existing clustering methods in an extensive simulation study covering known and unknown numbers of clusters. Real data sets are analysed, partly exploring the use of the new methods with non-Euclidean distances. The ASW is shown to satisfy some axioms that have been proposed for cluster quality functions. The new methods prove useful and sensible in many cases, but some weaknesses are also highlighted. These also concern the use of the ASW for estimating the number of clusters together with other methods, which is of general interest due to the popularity of the ASW for this task.
| Type: | Article |
|---|---|
| Title: | Clustering with the Average Silhouette Width |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.csda.2021.107190 |
| Publisher version: | https://doi.org/10.1016/j.csda.2021.107190 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Axiomatic clustering, Distance-based clustering, Partitioning around medoids, Number of clusters |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10126003 |
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