PDA

View Full Version : Chapter 4 - Overfitting


  1. Exercises and Problems
  2. Choice of regularization parameter
  3. Subdued inequalities
  4. How does deterministic noise cause overfitting?
  5. Overfitting with Polynomials : deterministic noise
  6. ERRATA: page 152
  7. What happens when error cannot be computed (is infinite) with leave-one-out CV?
  8. Is It Safe For Neophytes To Go Out And Use Regularization?
  9. Variance of Eval
  10. The expected validation error
  11. Deterministic Noise & Gibb's Phenomenon/Godunov's Theorem
  12. Zeroth regularization coefficient
  13. Typo
  14. Noise
  15. calculation 4.8 on p.139
  16. Chapter 4 Problem 4.4
  17. Exercise 4.7
  18. Data snooping
  19. Chosen #features for CV
  20. overfitting and spurious final hypothesis
  21. Figure 4.3(b)
  22. Problem 4.26
  23. Equation 4.13 calculating y_hat_n
  24. Problem 4.18
  25. Problem 4.21
  26. question about cross validation
  27. Exercise 4.10
  28. Exercise 4.4
  29. Exercise 4.6
  30. Cross validation estimate
  31. Multiple validation sets
  32. Eq. 4.3 in Exercise 4.4
  33. How does regularized logistic regression regularize perceptron model?
  34. Validaten and VC-Bound in practice
  35. specialized generalization bounds