Approximation Methods for Efficient Learning of Bayesian Networks.

This publication offers and investigates efficient Monte Carlo simulation methods in order to realize a Bayesian approach to approximate learning of Bayesian networks from both complete and incomplete data. For large amounts of incomplete data when Monte Carlo methods are inefficient, approximations...

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Bibliographic Details

Online Access:	Full Text (via ProQuest)
Main Author:	Riggelsen, C.
Other title:	Frontiers in Artificial Intelligence and Applications.
Format:	eBook
Language:	English
Published:	Amsterdam : IOS Press, 2008.
Series:	Frontiers in artificial intelligence and applications Approximation methods for efficient learning of Bayesian networks.
Subjects:	Bayesian statistical decision theory. Machine learning. Neural networks (Computer science)