Introduction to Bayesian Networks [Hardcover]

Finn V. Jensen (Author)

Book Description

ISBN-10: 0387915028 | ISBN-13: 978-0387915029 | Publication Date: August 15, 1997 | Edition: 1

In recent years Bayesian networks have attracted much attention in research institutions and industry. This book addresses persons who are interested in exploiting the Bayesian network approach for the construction of decision support systems or expert systems. The theoretical exposition of the book is self-contained and does not require any special mathematical prerequisites. The book includes a PC-diskette with a restricted version of HUGIN. The diskette includes a tool for building Bayesian networks, a library of examples, and a library of proposed solutions to some of the exercises.

Product Details

• Hardcover: 178 pages
• Publisher: Springer; 1 edition (August 15, 1997)
• Language: English
• ISBN-10: 0387915028
• ISBN-13: 978-0387915029
• Product Dimensions: 9 x 6.1 x 1 inches
• Shipping Weight: 1.2 pounds
• Average Customer Review: 4.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #2,599,779 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

19 of 20 people found the following review helpful:

4.0 out of 5 stars A starting book for Bayesian Network (BN), May 16, 2000

By A Customer

This review is from: Introduction to Bayesian Networks (Hardcover)

This book serves a good introductory material BN. After introducing the basic definitions and concepts, the author quickly cover most practical methods on model building, evidence propagation, and use of BN in finding explanation and making decisions. Most methods can easily be incorporated into your own applications if you are ready to program. There are plenty of examples that make me understand rules and concepts fast. Occasionally I found notations and proofs are difficult to follow. For reader who haven't become excited about BN, I strongly recommend Pearl's two books "Probabilistic reasoning in intelligent systems" and "Causations", which will surely entertain researchers from computer science, AI and statistics.