1 Fundamentals and definitions

Chapters in this book

1. Frontmatter I
2. Preface V
3. Preface of 2nd edition VII
4. Contents IX
5. List of Tables XIII
6. List of Figures XV
7. Notation XIX
8. Introduction XXIII
9. 1 Fundamentals and definitions 1
10. 2 Features 10
11. 3 Bayesian decision theory 103
12. 4 Parameter estimation 132
13. 5 Parameter free methods 161
14. 6 General considerations 180
15. 7 Special classifiers 191
16. 8 Classification with nominal features 257
17. 9 Classifier-independent concepts 273
18. A Solutions to the exercises 293
19. B A primer on Lie theory 307
20. C Random processes 311
21. Bibliography 315
22. Glossary 319
23. Index 325