Neural network architecture selection: new Bayesian perspectives in predictive modelling
作者： Jean-Pierre Vila , Vérène Wagner , Pascal Neveu , Marc Voltz , Philippe Lagacherie
DOI: 10.1016/S0304-3800(99)00096-4
关键词: Artificial intelligence 、 Predictive modelling 、 Machine learning 、 Selection (genetic algorithm) 、 Feedforward neural network 、 Operations research 、 Network architecture 、 Set (abstract data type) 、 Artificial neural network 、 Bayesian probability 、 Computer science 、 Bayesian inference 、 Ecological modelling
摘要: The aim of this paper is to present the community ecologists concerned with predictive modelling by feedforward neural network, a new statistical approach select best network architecture (number layers, number neurons per layer and connectivity) in set several candidate networks. interest demonstrated on soil hydrology problem.
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