Abstract
In this paper we propose two versions of Stacked Generalization as the combination module of an ensemble of neural networks. The first version only uses the information provided by expert networks. The second one uses the information provided by experts and the input data of the pattern that is being classified. Finally, we have performed a comparison among 6 classical combination methods and the two versions of Stacked Generalization in order to get the best method. The results show that the methods based on Stacked Generalization are better than classical combination methods.
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Hernández-Espinosa, C., Torres-Sospedra, J., Fernández-Redondo, M. (2006). Improving the Combination Module with a Neural Network. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_15
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DOI: https://doi.org/10.1007/11816157_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37271-4
Online ISBN: 978-3-540-37273-8
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