Bayesian Networks and Decision Graphs February 8, 2007 /

• Κύριοι συγγραφείς: Jensen, Finn V. (Συγγραφέας), Nielsen, Thomas D. (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: New York, NY : Springer New York, 2007.
• Έκδοση: Second Edition.
• Σειρά: Information Science and Statistics,
• Θέματα: Life sciences.; Mathematical statistics.; Artificial intelligence.; Plant science.; Botany.; Probabilities.; Statistics.; Life Sciences.; Plant Sciences.; Probability Theory and Stochastic Processes.; Probability and Statistics in Computer Science.; Artificial Intelligence (incl. Robotics).; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.

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 algor...

Πίνακας περιεχομένων:

• 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.