Bayesian Neural Networks
Bayesian techniques have been developed over many years in a range of different fields, but have only recently been applied to the problem of learning in neural networks. As well as providing a consistent framework for statistical pattern recognition, the Bayesian approach offers a number of practical advantages including a solution to the problem of over-fitting. This article provides an introductory overview of the application of Bayesian methods to neural networks. It assumes the reader is familiar with standard feed-forward network models and how to train them using conventional techniques
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| Format: | Digital revista |
| Language: | English |
| Published: |
Sociedade Brasileira de Computação
1997
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| Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65001997000200006 |
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