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» Model selection via Genetic Algorithms for RBF networks
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JIFS
2002
107views more  JIFS 2002»
13 years 4 months ago
Model selection via Genetic Algorithms for RBF networks
This work addresses the problem of finding the adjustable parameters of a learning algorithm using Genetic Algorithms. This problem is also known as the model selection problem. In...
Estefane G. M. de Lacerda, André Carlos Pon...
IJCNN
2008
IEEE
13 years 11 months ago
Fully complex-valued radial basis function networks for orthogonal least squares regression
— We consider a fully complex-valued radial basis function (RBF) network for regression application. The locally regularised orthogonal least squares (LROLS) algorithm with the D...
Sheng Chen, Xia Hong, Chris J. Harris
SBRN
2000
IEEE
13 years 9 months ago
Evolutionary Optimization of RBF Networks
One of the main obstacles to the widespread use of artijcial neural networks is the difJiculty of adequately define valuesfor their free parameters. This article discusses how Rad...
Estefane G. M. de Lacerda, Teresa Bernarda Ludermi...
ESANN
2008
13 years 6 months ago
Selection of important input variables for RBF network using partial derivatives
In regression problems, making accurate predictions is often the primary goal. Also, relevance of inputs in the prediction of an output would be valuable information in many cases....
Jarkko Tikka, Jaakko Hollmén
APIN
2005
127views more  APIN 2005»
13 years 4 months ago
Evolutionary Radial Basis Functions for Credit Assessment
Credit analysts generally assess the risk of credit applications based on their previous experience. They frequently employ quantitative methods to this end. Among the methods used...
Estefane G. M. de Lacerda, André Carlos Pon...