Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
Hierarchical Mixtures of Experts and the EM Algorithm
Hierarchical Mixtures of Experts and the EM Algorithm
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
Adaptive mixtures of local experts
Neural Computation
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A Modular Multi-Net System consists on some networks which solve partially a problem. The original problem has been decomposed into subproblems and each network focuses on solving a subproblem. The Mixture of Neural Networks consist on some expert networks which solve the subproblems and a gating network which weights the outputs of the expert networks. The expert networks and the gating network are trained all together in order to reduce the correlation among the networks and minimize the error of the system. In this paper we present the Mixture of Multilayer Feedforward (MixMF) a method based on MixNN which uses Multilayer Feedfoward networks for the expert level. Finally, we have performed a comparison among Simple Ensemble, MixNN and MixMF and the results show that MixMF is the best performing method.