Advances in Bayesian Networks:

In recent years probabilistic graphical models, especially Bayesian networks and decision graphs, have experienced significant theoretical development within areas such as Artificial Intelligence and Statistics. This carefully edited monograph is a compendium of the most recent advances in the area...

Full description

Saved in:
Bibliographic Details
Other Authors: Gámez, José A. (Editor), Moral, Serafín (Editor), Salmerón, Antonio (Editor)
Format: Electronic eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2004
Series:Studies in Fuzziness and Soft Computing 146
Subjects:
Online Access:FHI01
BTU01
Volltext
Summary:In recent years probabilistic graphical models, especially Bayesian networks and decision graphs, have experienced significant theoretical development within areas such as Artificial Intelligence and Statistics. This carefully edited monograph is a compendium of the most recent advances in the area of probabilistic graphical models such as decision graphs, learning from data and inference. It presents a survey of the state of the art of specific topics of recent interest of Bayesian Networks, including approximate propagation, abductive inferences, decision graphs, and applications of influence. In addition, "Advances in Bayesian Networks" presents a careful selection of applications of probabilistic graphical models to various fields such as speech recognition, meteorology or information retrieval
Physical Description:1 Online-Ressource (XI, 328 p)
ISBN:9783540398790
DOI:10.1007/978-3-540-39879-0

There is no print copy available.

Interlibrary loan Place Request Caution: Not in THWS collection! Get full text