Alberto Guillén, Héctor Pomares, Jesús González, Ignacio Rojas, L. J. Herrera, A. Prieto
Abstract. The design of Radial Basis Function Neural Networks (RBFNNs) still remains as a difficult task when they are applied to classification or to regression problems. The difficulty arises when...
A First Approach to Birth Weight Prediction Using RBFNNs (2008)
A. Guillén, I. Rojas, J. González, H. Pomares, L. J. Herrera
Abstract. This paper presents a first approach to try to determine the weight of a newborn using a set of variables determined uniquely by the mother. The proposed model to approximate the weight is...
A. Guillén, I. Rojas, J. González, H. Pomares, L. J. Herrera
Abstract. Nature shows many examples where the specialisation of elements aimed to solve different problems is successful. There are explorer ants, worker bees, etc., where a group of individuals is...
L. J. Herrera, H. Pomares, I. Rojas, O. Valenzuela, J. González, M. Awad
Abstract. This work introduces a modified Grid Based Fuzzy System architecture, which is especially suited for the problem of time series prediction. This new architecture overcomes the problem...
Effective Input Variable Selection for Function Approximation (2008)
L. J. Herrera, H. Pomares, I. Rojas, M. Verleysen, A. Guilén
Abstract. Input variable selection is a key preprocess step in any I/O modelling problem. Normally, better generalization performance is obtained when unneeded parameters coming from irrelevant or...
Feature selection using mutual information and neural networks (2006)
Pasadas, Miguel, Herrera, L.J., Valenzuela, O., Rojas, F., Guillén, A., Marquez, L.
Reducing the dimensionality of the raw input variable space is an important step in pattern recognition and functional approximation tasks often determined by practical feasibility. The purpose of...
I. Rojas, H. Pomares, J. Gonzalez, L. J. Herrera, A. Guillen, F. Rojas, ...
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Output Value-Based Initialization for Radial Basis Function Neural Networks (2005)
Alberto Guillén, Ignacio Rojas, Jesús González, Héctor Pomares, L. J. Herrera
The use of Radial Basis Function Neural Networks (RBFNNs) to solve functional approximation problems has been addressed many times in the literature. When designing an RBFNN to approximate a...
A Fuzzy-Possibilistic Fuzzy Ruled Clustering Algorithm for RBFNNs Design (2000)
A. Guillén, I. Rojas, J. González, H. Pomares, L. J. Herrera, A. Prieto
Abstract. This paper presents a new approach to the problem of designing Radial Basis Function Neural Networks (RBFNNs) to approximate a given function. The presented algorithm focuses in the first...
RBF CENTERS INITIALIZATION USING FUZZY CLUSTERING TECHNIQUE FOR FUNCTION APPROXIMATION PROBLEMS
Guillén, A., Rojas, I., González, J., Pomares, H., Herrera, L.J.
In this paper, a new algorithm for RBF centers initialization for functional approximation problems is proposed. The design of the algorithm is inspired in previous clustering algorithms but adding...