Learning Bayesian Networks

Learning Bayesian Networks (Artificial Intelligence)  

Posted by rainbowl76 at Jan. 13, 2009
Learning Bayesian Networks (Artificial Intelligence)

Learning Bayesian Networks (Artificial Intelligence)
Prentice Hall | 2003-04-06 | ISBN: 0130125342 | 678pages | PDF | 3.5MB
Approximation Methods for Efficient Learning of Bayesian Networks [Repost]

C. Riggelsen - Approximation Methods for Efficient Learning of Bayesian Networks
Published: 2008-01-15 | ISBN: 1586038214 | PDF | 148 pages | 1.27 MB
Approximation Methods for Efficient Learning of Bayesian Networks (repost)

Carsten Riggelsen - Approximation Methods for Efficient Learning of Bayesian Networks
English | 2008-01-15 | ISBN: 1586038214 | PDF | 148 pages | 1.27 MB

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. 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.

Learning Bayesian Models with R (Repost)  eBooks & eLearning

Posted by enmoys at May 26, 2016
Learning Bayesian Models with R (Repost)

Learning Bayesian Models with R By Dr. Hari M. Koduvely
2015 | 168 Pages | ISBN: 178398760X | EPUB | 3 MB
Advanced Methodologies for Bayesian Networks: Second International Workshop, AMBN 2015

Joe Suzuki and Maomi Ueno, "Advanced Methodologies for Bayesian Networks: Second International Workshop, AMBN 2015"
English | ISBN: 3319283782 | 2016 | 284 pages | PDF | 15 MB

Learning Bayesian Models with R [Repost]  eBooks & eLearning

Posted by tanas.olesya at April 5, 2016
Learning Bayesian Models with R [Repost]

Learning Bayesian Models with R by Dr. Hari M. Koduvely
English | 28 Oct. 2015 | ISBN: 178398760X | 191 Pages | EPUB | 3 MB

This book is for statisticians, analysts, and data scientists who want to build a Bayes-based system with R and implement it in their day-to-day models and projects. It is mainly intended for Data Scientists and Software Engineers who are involved in the development of Advanced Analytics applications.

Bayesian Networks and Decision Graphs  

Posted by step778 at Jan. 29, 2016
Bayesian Networks and Decision Graphs

Thomas Dyhre Nielsen, Finn Verner Jensen, "Bayesian Networks and Decision Graphs"
2007 | pages: 457 | ISBN: 0387682813 | PDF | 3,4 mb
Risk Assessment and Decision Analysis with Bayesian Networks (repost)

Norman Fenton and Martin Neil, "Risk Assessment and Decision Analysis with Bayesian Networks"
English | ISBN: 1439809100 | 2013 | 524 pages | PDF | 50 MB

"Bayesian Networks" ed. by Wichian Premchaiswadi  

Posted by exLib at Jan. 1, 2016
"Bayesian Networks" ed. by Wichian Premchaiswadi

"Bayesian Networks" ed. by Wichian Premchaiswadi
Second Edition
ITAvE | 2015 | ISBN: 9535105566 9789535105565 | 123 pages | PDF | 11 MB

Bayesian Belief Networks are a powerful tool for combining different knowledge sources with various degrees of uncertainty in a mathematically sound and computationally efficient way. A Bayesian network is a graphical model that encodes probabilistic relationships among variables of interest.

Learning Bayesian Models with R  

Posted by AlenMiler at Oct. 30, 2015
Learning Bayesian Models with R

Learning Bayesian Models with R by Dr. Hari M. Koduvely
English | 28 Oct. 2015 | ISBN: 178398760X | 168 Pages | AZW3 (Kindle)/HTML/EPUB/PDF (conv) | 19 MB

This book is for statisticians, analysts, and data scientists who want to build a Bayes-based system with R and implement it in their day-to-day models and projects. It is mainly intended for Data Scientists and Software Engineers who are involved in the development of Advanced Analytics applications.