Title | A Preliminar Analysis of CO2RBFN in Imbalanced Problems |
Publication Type | Conference Paper |
Year of Publication | 2009 |
Authors | Pérez-Godoy, M.D., Rivera-Rivas A.J., Fernández A., del Jesus M. J., and Herrera F. |
Editor | Cabestany, Joan, Sandoval Francisco, Prieto Alberto, and Corchado Juan M. |
Conference Name | Bio-Inspired Systems: Computational and Ambient Intelligence |
Pagination | 57–64 |
Publisher | Springer Berlin Heidelberg |
Conference Location | Berlin, Heidelberg |
ISBN Number | 978-3-642-02478-8 |
Abstract | In many real classification problems the data are imbalanced, i.e., the number of instances for some classes are much higher than that of the other classes. Solving a classification task using such an imbalanced data-set is difficult due to the bias of the training towards the majority classes. The aim of this contribution is to analyse the performance of CO2RBFN, a cooperative-competitive evolutionary model for the design of RBFNs applied to classification problems on imbalanced domains and to study the cooperation of a well known preprocessing method, the ``Synthetic Minority Over-sampling Technique'' (SMOTE) with our algorithm. The good performance of CO2RBFN is shown through an experimental study carried out over a large collection of imbalanced data-sets. |