On an adjacency cluster merit approach Online publication date: Sun, 11-Jan-2015
by Zeev Volkovich; Gerhard-Wilhelm Weber; Renata Avros; Orly Yahalom
International Journal of Operational Research (IJOR), Vol. 13, No. 3, 2012
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Operational Research (IJOR):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com