Approximation Methods for Efficient Learning of Bayesian Networks
Download or Read eBook Approximation Methods for Efficient Learning of Bayesian Networks PDF written by Carsten Riggelsen and published by IOS Press. This book was released on 2008 with total page 148 pages. Available in PDF, EPUB and Kindle.
Author | : Carsten Riggelsen |
Publisher | : IOS Press |
Total Pages | : 148 |
Release | : 2008 |
ISBN-10 | : 9781586038212 |
ISBN-13 | : 1586038214 |
Rating | : 4/5 (12 Downloads) |
Book Synopsis Approximation Methods for Efficient Learning of Bayesian Networks by : Carsten Riggelsen
Book excerpt: 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 are implemented, such that learning remains feasible, albeit non-Bayesian. The topics discussed are: basic concepts about probabilities, graph theory and conditional independence; Bayesian network learning from data; Monte Carlo simulation techniques; and, the concept of incomplete data. In order t.