Customer Reviews

Probabilistic Networks and Expert Systems: Exact Computational Methods for Bayesian Networks (Information Science and Statistics)

5 star:		(1)
4 star:		(0)
3 star:		(0)
2 star:		(0)
1 star:		(2)

 

 

This book starts with basic probabilistic concepts, graph theory, junction trees, conditional independence, to advanced topics related to learning Bayesian network. Many practical examples are clear and helpful. Good for graduate students of computer science and statistics.

This book focus on the inference process and parameter learning of bayesian netwroks, structure learning and model selection are only briefly sketched. Although incomplete, it covered enough materials as a introductory textbook in this field. Unfortuantely, however, its poor presentation may make it useless for either engineers or researchers in this field, the author hasn't given an understandable expliantion to any technical details, and the materials are not well organized.

I would like to recommend "learning bayesian network" , which covers almost all the necessary information as an introduction and all the materials are organized in an accessible way.

Too synthetic and technical to be used as an introduction to the subject, even for experienced statisticians and graduate students.