MARC details
| 000 -LEADER |
|---|
| fixed length control field |
04639nam a22005055i 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
978-0-387-68282-2 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20170628033325.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
|---|
| fixed length control field |
cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
100301s2007 xxu| s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9780387682822 |
| -- |
978-0-387-68282-2 |
| 024 7# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
10.1007/978-0-387-68282-2 |
| Source of number or code |
doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA276-280 |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
UYAM |
| Source |
bicssc |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
UFM |
| Source |
bicssc |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
COM077000 |
| Source |
bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
005.55 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Jensen, Finn V. |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Bayesian Networks and Decision Graphs |
| Medium |
[electronic resource] : |
| Remainder of title |
February 8, 2007 / |
| Statement of responsibility, etc |
by Finn V. Jensen, Thomas D. Nielsen. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
Second Edition. |
| 264 #1 - |
|---|
| -- |
New York, NY : |
| -- |
Springer New York, |
| -- |
2007. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
XVI, 448 p. |
| Other physical details |
online resource. |
| 336 ## - |
|---|
| -- |
text |
| -- |
txt |
| -- |
rdacontent |
| 337 ## - |
|---|
| -- |
computer |
| -- |
c |
| -- |
rdamedia |
| 338 ## - |
|---|
| -- |
online resource |
| -- |
cr |
| -- |
rdacarrier |
| 347 ## - |
|---|
| -- |
text file |
| -- |
PDF |
| -- |
rda |
| 490 1# - SERIES STATEMENT |
|---|
| Series statement |
Information Science and Statistics, |
| International Standard Serial Number |
1613-9011 |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Prerequisites on Probability Theory -- Prerequisites on Probability Theory -- Probabilistic Graphical Models -- Causal and Bayesian Networks -- Building Models -- Belief Updating in Bayesian Networks -- Analysis Tools for Bayesian Networks -- Parameter estimation -- Learning the Structure of Bayesian Networks -- Bayesian Networks as Classifiers -- Decision Graphs -- Graphical Languages for Specification of Decision Problems -- Solution Methods for Decision Graphs -- Methods for Analyzing Decision Problems. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. As modeling languages they allow a natural specification of problem domains with inherent uncertainty, and from a computational perspective they support efficient algorithms for automatic construction and query answering. This includes belief updating, finding the most probable explanation for the observed evidence, detecting conflicts in the evidence entered into the network, determining optimal strategies, analyzing for relevance, and performing sensitivity analysis. The book introduces probabilistic graphical models and decision graphs, including Bayesian networks and influence diagrams. The reader is introduced to the two types of frameworks through examples and exercises, which also instruct the reader on how to build these models. The book is a new edition of Bayesian Networks and Decision Graphs by Finn V. Jensen. The new edition is structured into two parts. The first part focuses on probabilistic graphical models. Compared with the previous book, the new edition also includes a thorough description of recent extensions to the Bayesian network modeling language, advances in exact and approximate belief updating algorithms, and methods for learning both the structure and the parameters of a Bayesian network. The second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision processes and partially ordered decision problems. The authors also provide a well-founded practical introduction to Bayesian networks, object-oriented Bayesian networks, decision trees, influence diagrams (and variants hereof), and Markov decision processes. give practical advice on the construction of Bayesian networks, decision trees, and influence diagrams from domain knowledge. < give several examples and exercises exploiting computer systems for dealing with Bayesian networks and decision graphs. present a thorough introduction to state-of-the-art solution and analysis algorithms. The book is intended as a textbook, but it can also be used for self-study and as a reference book. Finn V. Jensen is a professor at the department of computer science at Aalborg University, Denmark. Thomas D. Nielsen is an associate professor at the same department. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Statistics. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Probability and Statistics in Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Artificial Intelligence (incl. Robotics). |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Statistics for Engineering, Physics, Computer Science, Chemistry & Geosciences. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Nielsen, Thomas D. |
| Relator term |
author. |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY |
|---|
| Title |
Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Display text |
Printed edition: |
| International Standard Book Number |
9780387682815 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Information Science and Statistics, |
| -- |
1613-9011 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
<a href="http://dx.doi.org/10.1007/978-0-387-68282-2">http://dx.doi.org/10.1007/978-0-387-68282-2</a> |
| 912 ## - |
|---|
| -- |
ZDB-2-SCS |
