4. Parameter estimation

Kapitel in diesem Buch

1. Frontmatter I
2. Preface V
3. Contents VII
4. List of Tables XI
5. List of Figures XIII
6. Notation XVII
7. Introduction XIX
8. 1. Fundamentals and definitions 1
9. 2. Features 10
10. 3. Bayesian decision theory 98
11. 4. Parameter estimation 122
12. 5. Parameter free methods 142
13. 6. General considerations 162
14. 7. Special classifiers 173
15. 8. Classification with nominal features 215
16. 9. Classifier-independent concepts 231
17. A. Solutions to the exercises 249
18. B. A primer on Lie theory 263
19. C. Random processes 268
20. Bibliography 271
21. Glossary 275
22. Index 281