Abstract
This paper investigates the application of the mutual information for the evaluation of neuron inputs and for the selection of the relevant ones. The rules extraction method is based on the notion of weights templates, parameterizing regions of weights space using the mutual information criteria. The simulation results obtained with this method are very satisfactory.
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© 1998 Springer-Verlag Wien
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Nedjari, T. (1998). Use of Mutual Information to Extract Rules from Artificial Neural Networks. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6492-1_125
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DOI: https://doi.org/10.1007/978-3-7091-6492-1_125
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-83087-1
Online ISBN: 978-3-7091-6492-1
eBook Packages: Springer Book Archive