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Abstract
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| In this paper we apply Artificial Metaplasticity to a Multilayer Perceptron (MLP) for image classification. Artificial Metaplasticity is a novel Artificial Neural Network (ANN) training algorithm that gives more relevance to less frequent training patterns and subtracts relevance to the frequent ones during training phase, achieving a much more efficient training, while at least maintaining the MLP performance. In this paper, we test Metaplasticity MLP (MMLP) algorithm on an image standard data set: the Wisconsin Breast Cancer Database (WBCD). WBCD is a well-used database in Machine Learning, ANN and Signal Processing. Experimental results show that MMLPs reach better accuracy than any other recent results. | |
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International
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Si |
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Congress
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Industrial Informatics, 2009. INDIN 2009. 7th IEEE International Conference on |
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960 |
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Place
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Cardiff, UK |
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Reviewers
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Si |
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ISBN/ISSN
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1935-4576 |
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10.1109/INDIN.2009.5195879 |
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Start Date
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23/06/2009 |
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End Date
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26/06/2009 |
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From page
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650 |
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To page
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653 |
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Proc. of Industrial Informatics, 2009. INDIN 2009. 7th IEEE International Conference on |