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Descripción
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| In this paper we have presented a new method to extract knowledge from an existing data set, extracting symbolic rules from the weights of an Artificial Neural Network. The method has been applied with a neural network with special architecture Enhanced Neural Network (ENN). This architecture improves the results that have been obtained with multilayer perceptron (MLP). The relationship among the knowledge stored in the weights, the performance of the network and the new implemented algorithm to acquire rules from the weights is explained. The method itself gives a model to follow in the knowledge acquisition with ENN. | |
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Internacional
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Si |
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Nombre congreso
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INTERNATIONAL CONFERENCE ON COMPUTATIONAL AND APPLIED MATHEMATICAL METHODS IN SCIENCE AND ENGINERING CMMSE 2012. |
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Tipo de participación
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960 |
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Lugar del congreso
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Murcia |
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Revisores
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Si |
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ISBN o ISSN
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978-84-615-5392-1 |
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DOI
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Fecha inicio congreso
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02/07/2012 |
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Fecha fin congreso
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05/07/2012 |
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Desde la página
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1450 |
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Hasta la página
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1462 |
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Título de las actas
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Proceedings of the 2012 International Conference on Computational and Mathematical Methods in Science and Engineering Murcia, Spain July 2-5, 2012 |