A practical Bayesian framework for backpropagation networks
Neural Computation
The basic ideas in neural networks
Communications of the ACM
Neural networks: applications in industry, business and science
Communications of the ACM
Bayesian Learning for Neural Networks
Bayesian Learning for Neural Networks
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One of the most common problems encountered in agriculture is that of predicting a response variable from covariates of interest. The aim of this paper is to use a Bayesian neural network approach to predict dairy daughter milk production from dairy dam, sire, herd and environmental factors. The results of the Bayesian neural network are compared with the results obtained when the regression relationship is described using the traditional neural network approach. In addition, the "baseline" results of a multiple linear regression employing both frequentist and Bayesian methods are presented. The potential advantages of the Bayesian neural network approach over the traditional neural network approach are discussed.