On an adjacency cluster merit approach
Zeev Volkovich,
Gerhard-Wilhelm Weber,
Renata Avros and
Orly Yahalom
International Journal of Operational Research, 2012, vol. 13, issue 3, 239-255
Abstract:
This work addresses the cluster validation problem of determining the 'right' number of clusters. We consider a cluster stability property based on the k-nearest neighbour type coincidences model. Quality of a clustering is measured by the deviation from this model, where a small deviation indicates a good clustering. The true number of clusters corresponds to the empirical deviation distribution having the shortest right tail. Experiments carried out on synthetic and real data sets demonstrate the effectiveness of our method.
Keywords: clustering; cluster stability; two-sample test; data mining; nearest neighbours; cluster validation. (search for similar items in EconPapers)
Date: 2012
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=45663 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:13:y:2012:i:3:p:239-255
Access Statistics for this article
More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().