Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- 1 Introduction
- Part 1 Foundations
- 2 A Gentle Start
- 3 A Formal Learning Model
- 4 Learning via Uniform Convergence
- 5 The Bias-Complexity Trade-off
- 6 The VC-Dimension
- 7 Nonuniform Learnability
- 8 The Runtime of Learning
- Part 2 From Theory to Algorithms
- Part 3 Additional Learning Models
- Part 4 Advanced Theory
- Appendix A Technical Lemmas
- Appendix B Measure Concentration
- Appendix C Linear Algebra
- References
- Index
5 - The Bias-Complexity Trade-off
from Part 1 - Foundations
Published online by Cambridge University Press: 05 July 2014
- Frontmatter
- Dedication
- Contents
- Preface
- 1 Introduction
- Part 1 Foundations
- 2 A Gentle Start
- 3 A Formal Learning Model
- 4 Learning via Uniform Convergence
- 5 The Bias-Complexity Trade-off
- 6 The VC-Dimension
- 7 Nonuniform Learnability
- 8 The Runtime of Learning
- Part 2 From Theory to Algorithms
- Part 3 Additional Learning Models
- Part 4 Advanced Theory
- Appendix A Technical Lemmas
- Appendix B Measure Concentration
- Appendix C Linear Algebra
- References
- Index
Summary
- Type
- Chapter
- Information
- Understanding Machine LearningFrom Theory to Algorithms, pp. 36 - 42Publisher: Cambridge University PressPrint publication year: 2014