Bio-inspired parameter tunning of MLP networks for gene expression analysis

• Type: Chapter or Part of a Book
• Date: 2008

Authors

Rossi, ALD (Author) Other; Carvalho, ACPLF (Author) Other; Soares, C (Author) FEP

Book

Title: Proceedings - 8Th International Conference on Hybrid Intelligent Systems, His 2008

Pages: 435-440

ISBN: 9780769533261

Indexing

ISI Web of Knowledge

Scopus - 5 Citations

Other information

Authenticus ID: P-007-NSN

DOI: 10.1109/his.2008.152

Abstract (EN): 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. © 2008 IEEE.

Language: English

Type (Professor's evaluation): Scientific

Notes: 8th International Conference on Hybrid Intelligent Systems, HIS 2008 Barcelona, 10 September 2008 through 12 September 2008