A Statistically-Based Approach to Feedforward Neural Network Model Selection

A novel model selection method is proposed for feedforward neural networks that performs both input- and hidden-node selection using the Bayesian information criterion (BIC) to achieve parsimonious models without compromising out-of-sample performance.