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
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICHIS.2005.5
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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||