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View Full Version : Chapter 5 - Three Learning Principles


  1. Exercises and Problems
  2. Cross validation and data snooping
  3. Data snooping (test vs. train data)
  4. Sampling bias and class imbalance for target variable
  5. Data snooping and non-linear transformation
  6. Input normalization
  7. Ecv versus Eout versus Etest
  8. Problem 5.1b
  9. Relative size of data set v/s test set
  10. Data Snooping with Test Set Inputs Intuition
  11. Snooping and unsupervised preprocessing
  12. How to solve example 5.3 step per step?