Demonstration of the Bayesian Evidence Scheme for Regularisation

The Bayesian evidence approach to regularisation, derived in the previous chapter, is applied to the stochastic time series generated from the logistic-kappa map. The scheme is found to prevent overfitting and lead to a stabilisation of the training process with respect to changes in the length of training time. For a small training set, it is also found to include an automatic pruning scheme: the network complexity is reduced until all remaining parameters are well-determined by the data.