A mutual information based online evolving clustering approach and its applications

A mutual information based online evolving clustering approach and its applications In this article, a new recursive evolving clustering method is proposed based on the well-known Gustafson–Kessel algorithm. The novelty of the proposed method involves the adaptation and integration of the mutual information based formulation to accommodate the Mahalanobis distance, which functions as the similarity measure and the unification of the clustering generation and pruning mechanisms. Example applications of the method are also discussed in the areas of data compression and knowledge extraction. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Evolving Systems Springer Journals

A mutual information based online evolving clustering approach and its applications

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2017 by Springer-Verlag GmbH Germany
Subject
Engineering; Complexity; Artificial Intelligence (incl. Robotics); Complex Systems
ISSN
1868-6478
eISSN
1868-6486
D.O.I.
10.1007/s12530-017-9191-y
Publisher site
See Article on Publisher Site

Abstract

In this article, a new recursive evolving clustering method is proposed based on the well-known Gustafson–Kessel algorithm. The novelty of the proposed method involves the adaptation and integration of the mutual information based formulation to accommodate the Mahalanobis distance, which functions as the similarity measure and the unification of the clustering generation and pruning mechanisms. Example applications of the method are also discussed in the areas of data compression and knowledge extraction.

Journal

Evolving SystemsSpringer Journals

Published: Jul 15, 2017

References

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