稽核項 
1 online resource (xxvii, 463 p.) : ill 
叢書名 
Chapman & Hall/CRC computer science and data analysis series 

Series in computer science and data analysis

內容 
I. PROBABILISTIC REASONING: Bayesian reasoning  Introducing Bayesian networks  Inference in Bayesian networks  Decision networks  Applications of Bayesian networks  II. LEARNING CAUSAL MODELS: Learning probabilities  Bayesian network classifiers  Learning linear causal models  Learning discrete causal structure  III. KNOWLEDGE ENGINEERING: Knowledge engineering with Bayesian networks  KEBN case studies 
附註 
"Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology. New to the Second Edition New chapter on Bayesian network classifiers New section on objectoriented Bayesian networks New section that addresses foundational problems with causal discovery and Markov blanket discovery New section that covers methods of evaluating causal discovery programs Discussions of many common modeling errors New applications and case studies More coverage on the uses of causal interventions to understand and reason with causal Bayesian networks Illustrated with real case studies, the second edition of this bestseller continues to cover the groundwork of Bayesian networks. It presents the elements of Bayesian network technology, automated causal discovery, and learning probabilities from data and shows how to employ these technologies to develop probabilistic expert systems. Web Resource The books website at www.csse.monash.edu.au/bai/book/book.html offers a variety of supplemental materials, including example Bayesian networks and data sets. Instructors can email the authors for sample solutions to many of the problems in the text"Provided by publisher 

"The second edition of this bestseller provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. This edition contains a new chapter on Bayesian network classifiers and a new section on objectoriented Bayesian networks, along with new applications and case studies. It includes a new section that addresses foundational problems with causal discovery and Markov blanket discovery and a new section that covers methods of evaluating causal discovery programs. The book also offers more coverage on the uses of causal interventions to understand and reason with causal Bayesian networks. Supplemental materials are available on the book's website"Provided by publisher 

Description based on print version record 
主題 
Bayes Theorem


Statistics at Topic


Artificial Intelligence


Neural Networks (Computer)


Bayesian statistical decision theory  Data processing


Machine learning


Neural networks (Computer science)


Electronic books 
其他作者 
Nicholson, Ann E

國際標準書號 
9781439815922 (electronic bk.) 

1439815925 (electronic bk.) 
