Bayesian networks and decision graphs
โ Finn B. Jensen, Thomas Graven-Nielsen
๐ Library
๐
2007
๐ Springer
๐ English
โฆ LIBER โฆ
๐
Bayesian Networks and Decision Graphs
โ Scribed by Finn V. Jensen (auth.)
- Publisher
- Springer New York
- Year
- 2001
- Tongue
- English
- Leaves
- 279
- Series
- Statistics for Engineering and Information Science
- Category
- Library
โฌ Acquire This Volume
No coin nor oath required. For personal study only.
โฆ Table of Contents
Front Matter....Pages i-xv
Front Matter....Pages 1-1
Causal and Bayesian Networks....Pages 3-34
Building Models....Pages 35-78
Learning, Adaptation, and Tuning....Pages 79-107
Decision Graphs....Pages 109-155
Front Matter....Pages 157-157
Belief Updating in Bayesian Networks....Pages 159-200
Bayesian Network Analysis Tools....Pages 201-224
Algorithms for Influence Diagrams....Pages 225-252
Back Matter....Pages 253-268
โฆ Subjects
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Artificial Intelligence (incl. Robotics); Probability and Statistics in Computer Science
๐ SIMILAR VOLUMES
Bayesian Networks and Decision Graphs
โ Finn B. Jensen, Thomas Graven-Nielsen
๐ Library
๐
2007
๐ Springer
๐ English
<P>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 al
Bayesian Networks and Decision Graphs: F
โ Finn V. Jensen, Thomas D. Nielsen (auth.)
๐ Library
๐
2007
๐ Springer-Verlag New York
๐ English
<p><P>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
Bayesian Networks & Bayeslab
โ it-ebooks
๐ Library
๐
2018
๐ iBooker it-ebooks
๐ English
Risk assessment and decision analysis wi
โ Fenton, Norman; Neil, Martin
๐ Library
๐
2019
๐ Chapman & Hall/CRC
๐ English
Since the first edition of this book published, Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams, learning from data, value of information, cybersecurity, debunking bad statistics, and much m
Risk assessment and decision analysis wi
โ Fenton, Norman; Neil, Martin
๐ Library
๐
2019
๐ Chapman & Hall/CRC
๐ English
Since the first edition of this book published, Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams, learning from data, value of information, cybersecurity, debunking bad statistics, and much m