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Descripción
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| This paper tests a novel improvement in neural network training by implementing Metaplasticity Multilayer Perceptron (MMLP) Neural Networks (NNs), that are based on the biological property of metaplasticity. Artificial Metaplasticity bases its efficiency in giving more relevance to the less frequent patterns and subtracting relevance to the more frequent ones. The statistical distribution of training patterns is used to quantify how frequent a pattern is. We model this interpretation in the NNs training phase. Wisconsin breast cancer database (WBCD) was used to train and test MMLP. Our results were compared to recent research results on the same database, proving to be superior or at least an interesting alternative | |
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Internacional
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Si |
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Nombre congreso
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IWANN 09 |
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Tipo de participación
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960 |
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Lugar del congreso
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Salamanca |
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Revisores
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Si |
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ISBN o ISSN
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978-3-642-02477-1 |
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DOI
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10.1007/978-3-642-02478-8 |
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Fecha inicio congreso
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10/06/2009 |
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Fecha fin congreso
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12/06/2009 |
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Desde la página
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174 |
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Hasta la página
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179 |
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Título de las actas
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Bio-Inspired Systems : Computational and Ambient Intelligence. LCNS 5517 |