Error analysis in artificial neural networks: the imbalanced distribution case

Authors:
R. Alejo;J. M. Sotoca;M. G. De La Rosa
Affiliations:
UAEM, CU UAEM Atlacomulco, Mexico;Universitat Jaume I, Dept. Lenguajes y Sistemas Informáticos, Castelló, Spain;UAEM, CU UAEM Atlacomulco, Mexico
Venue:
SMO'08 Proceedings of the 8th conference on Simulation, modelling and optimization
Year:
2008

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Abstract

A comparative empirical study is presented using different cost functions designed to reduce the imbalanced class influence in the training data. This work is focused in the learning and classification process by using perceptron multilayer and radial basis functions neural networks. This artificial neural networks were trained by means of the back-propagation algorithm in batch mode using two class databases.