The mixture of neural networks as ensemble combiner

Abstract

In this paper we propose two new ensemble combiners based on the Mixture of Neural Networks model. In our experiments, we have applied two different network architectures on the methods based on the Mixture of Neural Networks: the Basic Network (BN) and the Multilayer Feedforward Network (MF). Moreover, we have used ensembles of MF networks previously trained with Simple Ensemble to test the performance of the combiners we propose. Finally, we compare the mixture combiners proposed with three different mixture models and other traditional combiners. The results show that the mixture combiners proposed are the best way to build Multi-net systems among the methods studied in the paper in general. © 2008 Springer-Verlag Berlin Heidelberg.