loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Fifth International Conference on Hybrid Intelligent Systems (HIS'05)
A Fuzzy c-means Algorithm Based on an Adaptive L2 Minkowsky Distance
Rio de Janeiro, Brazil
December 06-December 09
ISBN: 0-7695-2457-5
Nicomedes L. Cavalcanti Junior, Centro de Informatica - CIn / UFPE, Brazil
An extension of the fuzzy c-means clustering algorithm based on an adaptive distance is presented. The proposed method furnishes a fuzzy partition and a prototype for each cluster by optimizing a criterion based on an adaptive L2 Minkowsky distance that changes at each algorithm?s iteration. Experiments with real and synthetic data sets show the usefulness of this method.
Citation:
Nicomedes L. Cavalcanti Junior, "A Fuzzy c-means Algorithm Based on an Adaptive L2 Minkowsky Distance," his, pp.104-109, Fifth International Conference on Hybrid Intelligent Systems (HIS'05), 2005
Usage of this product signifies your acceptance of the Terms of Use.