Symbolic interpretation of artificial neural networks using genetic algorithms

Authors : Dounia YEDJOUR, Abdelkader BENYETTOU, Hayat YEDJOUR

Pages : 2465-2475

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Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :The knowledge acquired during the learning of artificial neural networks insert ignore into journalissuearticles values(ANNs); is coded as values in synaptic weights, which makes their interpretations difficult, hence the name of the black box. The aim of this work is to provide a comprehensible interpretation of the ANN`s decisions by extracting symbolic rules. We improve the performance of our extraction algorithm by combining the ANN with a genetic algorithm. Misleading rules whose support and confidence values are less than fixed thresholds are removed and, as a result, the comprehensibility is improved. The extracted rules are evaluated and compared with other works. The results show good performance of our proposal in terms of fidelity and accuracy.
Keywords : Neural networks, rule extraction, genetic algorithm