Incremental rule pruning for fuzzy ARTMAP neural network

Authors:
A. Andrés-Andrés;E. Gómez-Sánchez;M. L. Bote-Lorenzo
Affiliations:
School of Telecommunications Engineering, University of Valladolid, Valladolid, Spain;School of Telecommunications Engineering, University of Valladolid, Valladolid, Spain;School of Telecommunications Engineering, University of Valladolid, Valladolid, Spain
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Year:
2005

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Abstract

Fuzzy ARTMAP is capable of incrementally learning interpretable rules. To remove unused or inaccurate rules, a rule pruning method has been proposed in the literature. This paper addresses its limitations when incremental learning is used, and modifies it so that it does not need to store previously learnt samples. Experiments show a better performance, especially in concept drift problems.