Title :
Bayesian learning for time series prediction with exogenous variables
Author :
Crucianu, Michel ; Boné, Romuald ; De Beauville, Jean-Pierre Asselin
Author_Institution :
Lab. d´´Inf., Univ. de Tours, France
Abstract :
We extend the Bayesian learning framework to the modelling of multivariate time series with feedforward neural networks. The extension presented here concerns both regression and classification problems. Finally, we present preliminary results regarding the choice of appropriate priors for building such sequential models
Keywords :
Bayes methods; feedforward neural nets; learning (artificial intelligence); pattern classification; prediction theory; statistical analysis; time series; Bayesian learning; exogenous variables; feedforward neural networks; multivariate regression; pattern classification; time series prediction; Bayesian methods; Bones; Computer networks; Feedforward neural networks; Feedforward systems; Information resources; Linearity; Neural networks; Predictive models; Probability distribution;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.833484
