Knowledge extraction from neural networks using the all-permutations fuzzy rule base: the LED display recognition problem

Authors:
Eyal Kolman;Michael Margaliot
Affiliations:
School of Electrical Engineering, Tel-Aviv University, Tel-Aviv, Israel;School of Electrical Engineering, Tel-Aviv University, Tel-Aviv, Israel
Venue:
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Year:
2005

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Abstract

A major drawback of artificial neural networks is their black-box character. In this paper, we use the equivalence between artificial neural networks and a specific fuzzy rule base to extract the knowledge embedded in the network. We demonstrate this using a benchmark problem: the recognition of digits produced by a LED device. The method provides a symbolic and comprehensible description of the knowledge learned by the network during its training.