Dynamic pruning algorithms for improving generalisation of neural networks
In this paper, we study the effects of pruning on the generalisation performance of feed-forward networks. The weighted sensitivity method and ratio dependent sensitivity method are proposed to efficiently prune a given network. Pruning criteria using statistical methods are also discussed and experimental results are presented to illustrate their effects on the generalisation property of the network.