| 000 -LEADER |
|---|
| fixed length control field |
02931nam a22003375i 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
978-0-387-74101-7 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20161121231208.0 |
| 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 |
100301s2008 xxu| s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9780387741017 |
| -- |
978-0-387-74101-7 |
| 024 7# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
10.1007/978-0-387-74101-7 |
| 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 |
UFM |
| Source |
bicssc |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
COM077000 |
| Source |
bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
519.5 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Kj�rulff, Uffe B. |
| Relator term |
author.1 |
| 245 0# - TITLE STATEMENT |
|---|
| Title |
Bayesian Networks and Influence Diagrams |
| Medium |
[electronic resource] : |
| Remainder of title |
A Guide to Construction and Analysis / |
| Statement of responsibility, etc. |
by Uffe B. Kj�rulff, Anders L. Madsen. 1 |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
New York, NY : |
| Name of producer, publisher, distributor, manufacturer |
Springer New York, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2008. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
XVIII, 318 p. |
| Other physical details |
online resource. |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
computer |
| Media type code |
c |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
online resource |
| Carrier type code |
cr |
| Source |
rdacarrier |
| 347 ## - DIGITAL FILE CHARACTERISTICS |
|---|
| File type |
text file |
| Encoding format |
PDF |
| Source |
rda1 |
| 490 ## - SERIES STATEMENT |
|---|
| Series statement |
Information Science and Statistics, |
| International Standard Serial Number |
1613-90110 |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Fundamentals -- Networks -- Probabilities -- Probabilistic Networks -- Solving Probabilistic Networks -- Model Construction -- Eliciting the Model -- Modeling Techniques -- Data-Driven Modeling -- Model Analysis -- Conflict Analysis -- Sensitivity Analysis -- Value of Information Analysis. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification, troubleshooting, and data mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his/her level of understanding. The techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined on the basis of numerous courses that the authors have held for practitioners worldwide. Uffe B. Kj�rulff holds a PhD on probabilistic networks and is an Associate Professor of Computer Science at Aalborg University. Anders L. Madsen holds a PhD on probabilistic networks and is the CEO of HUGIN Expert A/S. 0 |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Relator term |
author.2 |
| 776 ## - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| International Standard Book Number |
9780387741000 0 |
| 830 ## - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| International Standard Serial Number |
1613-901140 |
