An introduction to computational learning theory /
Збережено в:
| Автор: | |
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| Інші автори: | |
| Формат: | Книга |
| Мова: | English |
| Опубліковано: |
Cambridge, Mass. :
MIT Press,
c1994.
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| Предмети: |
Зміст:
- 1. The Probably Approximately Correct Learning Model
- 2. Occam's Razor
- 3. The Vapnik-Chervonenkis Dimension
- 4. Weak and Strong Learning
- 5. Learning in the Presence of Noise
- 6. Inherent Unpredictability
- 7. Reducibility in PAC Learning
- 8. Learning Finite Automata by Experimentation
- 9. Appendix: Some Tools for Probabilistic Analysis.