Analysis of sampling methods in the learning process of ensemble neural networks

Abstract

When developing learning algorithms for ensemble neural networks it is of fundamental importance to use a sampling method. In this paper a comparative analysis is made, between a sampling data method based on the mean square error for the training of ensemble neural networks and cross validation sampling method.