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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Gámez, José A. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Moral, Serafin (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Salmerón Cerdan, Antonio (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2004.
Έκδοση:1st ed. 2004.
Σειρά:Studies in Fuzziness and Soft Computing, 146
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Περιγραφή
Περίληψη: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.
Φυσική περιγραφή:XI, 328 p. online resource.
ISBN:9783540398790
ISSN:1434-9922 ;
DOI:10.1007/978-3-540-39879-0