Fuzzy c-means density based clustering using data induced metric

Beliakov, Gleb and King, Matthew 2005, Fuzzy c-means density based clustering using data induced metric, in Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, ACTA Press, Anaheim, CA, pp. 234-239.

Attached Files
Name Description MIMEType Size Downloads

Title Fuzzy c-means density based clustering using data induced metric
Author(s) Beliakov, Gleb
King, Matthew
Conference name Artificial Intelligence and Applications (2005 : Innsbruck, Austria)
Conference location Innsbruck, Austria
Conference dates 14-16 February 2005
Title of proceedings Proceedings of the IASTED International Conference on Artificial Intelligence and Applications
Editor(s) Hamza, M.H.
Publication date 2005
Conference series International Association of Science and Technology for Development Conference on Artficial Intelligence and Applications
Start page 234
End page 239
Publisher ACTA Press
Place of publication Anaheim, CA
Keyword(s) clustering
unsupervised classification
fuzzy c-means
data induced metric
density estimation
Summary We propose a new data induced metric to perform un supervised data classification (clustering). Our goal is to automatically recognize clusters of non-convex shape. We present a new version of fuzzy c-means al gorithm, based on the data induced metric, which is capable to identify non-convex d-dimensional clusters.
ISBN 0889864578
9780889864573
Language eng
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2005, ACTA Press
Persistent URL http://hdl.handle.net/10536/DRO/DU:30005761

Document type: Conference Paper
Collection: School of Information Technology
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Access Statistics: 404 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Mon, 07 Jul 2008, 09:53:52 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.