Hierarchical Model Selection for NGnet Based on Variational Bayes Inference

This article presents a variational Bayes inference for normalized Gaussian network, which is a kind of mixture models of local experts. In order to search for the optimal model structure, we develop a hierarchical model selection method. The performance of our method is evaluated by using function approximation and nonlinear dynamical system identification problems. Our method achieved better performance than existing methods.