Probabilistic networks and expert systems : exact computational methods for Bayesian networks
Author(s)
Bibliographic Information
Probabilistic networks and expert systems : exact computational methods for Bayesian networks
（Information science and statistics / series editors M. Jordan ... [et al.]）
Springer, c2007
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Note
Other authors: A. Philip Dawid, Steffen L. Lauritzen, David J. Spiegelhalter
Includes bibliographical references (p. [281]-305) and indexes
Description and Table of Contents
Description
Probabilistic expert systems are graphical networks which support the modeling of uncertainty and decisions in large complex domains, while retaining ease of calculation. Building on original research by the authors, this book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures, and algorithms. The book will be of interest to researchers in both artificial intelligence and statistics, who desire an introduction to this fascinating and rapidly developing field. The book, winner of the DeGroot Prize 2002, the only book prize in the field of statistics, is new in paperback.
Table of Contents
Logic, Uncertainty, and Probability.- Building and Using Probabilistic Networks.- Graph Theory.- Markov Properties on Graphs.- Discrete Networks.- Gaussian and Mixed Discrete-Gaussian Networks.- Discrete Multistage Decision Networks.- Learning About Probabilities.- Checking Models Against Data.- Structural Learning.
by "Nielsen BookData"
