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Learning Bayesian Networks

By Richard E. Neapolitan

Published by Pearson

Published Date: May 14, 2019

Table of Contents



Preface.

I. BASICS.

 1. Introduction to Bayesian Networks.

 2. More DAG/Probability Relationships.

II. INFERENCE.

 3. Inference: Discrete Variables.

 4. More Inference Algorithms.

 5. Influence Diagrams.

III. LEARNING.

 6. Parameter Learning: Binary Variables.

 7. More Parameter Learning.

 8. Bayesian Structure Learning.

 9. Approximate Bayesian Structure Learning.

10. Constraint-Based Learning.

11. More Structure Learning.

IV. APPICATIONS.

12. Applications.

Bibliography.

Index.

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Learning Bayesian Networks

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