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2008

Bio-Inspired Parameter Tunning of MLP Networks for Gene Expression Analysis

11 years 8 months ago
Bio-Inspired Parameter Tunning of MLP Networks for Gene Expression Analysis
The performance of Artificial Neural Networks is largely influenced by the value of their parameters. Among these free parameters, one can mention those related with the network architecture, e.g., number of hidden neurons, number of hidden layers, activation function, and those associated with a learning algorithm, e.g., learning rate. Optimization techniques, often Genetic Algorithms, have been used to tune neural networks parameter values. Lately, other techniques inspired in Biology have been investigated. In this paper, we compare the influence of different bio-inspired optimization techniques on the accuracy obtained by the networks in the domain of gene expression analysis. The experimental results show the potential of use this techniques for parameter tuning of neural networks.
André L. D. Rossi, André C. P. L. F.
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where HIS
Authors André L. D. Rossi, André C. P. L. F. Carvalho, Carlos Soares
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