Bayesian networks and decision graphs
โ Scribed by Finn B. Jensen, Thomas Graven-Nielsen
- Publisher
- Springer
- Year
- 2007
- Tongue
- English
- Leaves
- 457
- Series
- Information Science and Statistics
- Edition
- 2nd
- Category
- Library
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
<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
<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
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
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