A simple strategy to prune neural networks with an application to economic time series

A major problem in applying neural networks is specifying the size of the network. Even for moderately sized networks the number of parameters may become large compared to the number of data. In this paper network performance is examined while reducing the size of the network through the use of multiple correlation coefficients, principal component analysis of residuals and graphical analysis of network output per hidden layer cell and input layer cell.