Bayesian Networks and Decision Graphs
Jensen, Finn V.
Venduto da Florida Mountain Book Co., Datil, NM, U.S.A.
Venditore AbeBooks dal 3 giugno 1999
Usato - Rilegato
Condizione: Usato - Molto buono
Quantità: 1 disponibili
Aggiungere al carrelloVenduto da Florida Mountain Book Co., Datil, NM, U.S.A.
Venditore AbeBooks dal 3 giugno 1999
Condizione: Usato - Molto buono
Quantità: 1 disponibili
Aggiungere al carrelloHardcover, [xv], 268 pages. Very Good condition. First printing. Size 9.5"x6.25". "The book emphasizes both the human and the computer side. Part I gives a thorough introduction to Bayesian networks as well as decision trees and infulence diagrams, and through examples and exercises, the reader is instructed in building graphical models from domain knowledge. This part is self-contained and it does not require other background than standard secondary school mathematics. Part II is devoted to the presentation of algorithms and complexity issues. This part is also self-contained, but it requires that the reader is familiar with working with texts in the mathematical language." Book has light handling/shelfwear, spine is sunned, else Fine condition, clean and unmarked.
Codice articolo 009774
From the reviews:
MATHEMATICAL REVIEWS
"This is indeed an invaluable text for students in information technology, engineering, and statistics. It is also very helpful for researchers in these fields and for those working in industry. The book is self-contained...The book has enough illustrative examples and exercises for the reader. All the illustrations are motivated by real applications. Moreover, the book provides a good balance between pure mathematical treatment and the applied aspects of the subject."
"The Bayesian network (BN), or probabilistic expert system, is technology for automating human-life reasoning under uncertainty in specific contexts. ... the book does an admirable job of concisely explaining a great range of concepts and techniques. ... the book is very well written and to my knowledge nothing else meets its specific goal of quickly equipping the reader with both practical skills and sufficient theoretical background. ... I certainly would not want to try to implement a BN application without reading this book.” (David Tritchler, Sankhya: Indian Journal of Statistics, Vol. 64 (B Part 3), 2002)
"Professor Jensen is certainly one of the most influential researchers in the field of Bayesian networks and it is not surprising that this book represents a very clear and useful presentation of the main properties and use of graphical models. ... I think that the present volume represents a useful integration of other material and a compact guide for either a student who wants an introduction to the field or a teacher who needs a reference for a course on probabilistic reasoning in AI." (Luigi Portinale, The Computer Journal, Vol. 46 (3), 2003)
"This book is an introduction to Bayesian networks at an accessible level for first-year graduate or advanced undergraduate students. ... I found this book to be an excellent introduction to the topic. It is well written, provides broad topic coverage, and is quite accessible to the non-expert. ... I think Bayesian Networks and Decision Graphs would make a fine text for an introductory class in Bayesian networks or a useful reference for anyone interested in learning about the field." (David J. Marchette, Technometrics, Vol. 45 (2), 2003)
"I can comfortably recommend this book as a primary source for topics related to Bayesian networks and decision graphs. This would be an excellent edition to any personal library." (Technometrics, Feburary 2008)
From the reviews of the second edition:
"The present book provides a very readable but also rigorous and comprehensive introduction to the subject. It would make a very good text for a graduate or an advanced undergraduate course. ... Altogether, this is a very useful book for anyone interested in learning Bayesian networks without tears." (Jayanta K. Ghosh, International Statistical Reviews, Vol. 76 (2), 2008)
"This book is the second edition of Jensen’s Bayesian Networks and Decision Graphs ... . Each chapter ends with a summary section, bibliographic notes, and exercises. ... provides a readable, self-contained, and above all, practical introduction to Bayesian networks and decision graphs. Its treatment is appropriate not just for statisticians, but also for computer scientists, engineers, and others researchers with appropriate mathematical background. ... highly recommend it as a text or a useful reference for anyone interested in probabilistic graphical models or decision graphs." (Alyson G. Wilson, Journal of the American Statistical Association, Vol. 104 (485), March, 2009)
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