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Knowledge Extraction From Neural Networks Using the All-Permutations Fuzzy Rule Base: The LED Display Recognition Problem

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2 Author(s)
Eyal Kolman ; Sch. of Electr. Eng.-Syst., Tel Aviv Univ. ; Michael Margaliot

A major drawback of artificial neural networks (ANNs) is their black-box character. Even when the trained network performs adequately, it is very difficult to understand its operation. In this letter, we use the mathematical equivalence between ANNs 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 light emitting diode (LED) device. The method provides a symbolic and comprehensible description of the knowledge learned by the network during its training

Published in:

IEEE Transactions on Neural Networks  (Volume:18 ,  Issue: 3 )