Semantic Scholar Open Access 2007 2822 sitasi

Learning Bayesian networks

R. Neapolitan

Abstrak

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.

Topik & Kata Kunci

Computer Science Mathematics

Penulis (1)

R. Neapolitan

Format Sitasi

APA MLA BibTeX

Neapolitan, R. (2007). Learning Bayesian networks. https://doi.org/10.1145/1327942.1327961

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Informasi Jurnal

Tahun Terbit: 2007
Bahasa: en
Total Sitasi: 2822×
Sumber Database: Semantic Scholar
DOI: 10.1145/1327942.1327961
Akses: Open Access ✓