Finding the number of disparate clusters with background contamination
Atkinson, A. C., Cerioli, A., Morelli, G. & Riani, M.
(2015).
Finding the number of disparate clusters with background contamination.
In
Lausen, B., Krolak-Schwerdt, S. & Böhmer, M.
(Eds.),
Data Science, Learning by Latent Structures, and Knowledge Discovery
(pp. 29-42).
Springer Berlin / Heidelberg.
https://doi.org/10.1007/978-3-662-44983-7
The Forward Search is used in an exploratory manner, with many random starts, to indicate the number of clusters and their membership in continuous data. The prospective clusters can readily be distinguished from background noise and from other forms of outliers. A confirmatory Forward Search, involving control on the sizes of statistical tests, establishes precise cluster membership. The method performs as well as robust methods such as TCLUST. However, it does not require prior specification of the number of clusters, nor of the level of trimming of outliers. In this way it is “user friendly”.
| Item Type | Chapter |
|---|---|
| Copyright holders | © 2015 Springer-Verlag Berlin Heidelberg |
| Departments | LSE > Academic Departments > Statistics |
| DOI | 10.1007/978-3-662-44983-7 |
| Date Deposited | 19 Sep 2016 |
| URI | https://researchonline.lse.ac.uk/id/eprint/67782 |
Explore Further
- http://link.springer.com/book/10.1007%2F978-3-662-44983-7 (Publisher)
- http://www.lse.ac.uk/Statistics/People/Professor-Anthony-Atkinson.aspx (Author)
- https://www.scopus.com/pages/publications/84945556075 (Scopus publication)
- http://www.springer.com/ (Official URL)