Chapter : Lesson 2

Episode 7 - Train and Test Distributions

face Josiah Wang

Summary:

  • You can consider the scores/errors on the training or test sets.
  • High training error:
    • Possibly underfitting (high bias)
    • Bias can be seen as the training error
  • Low training error, high test error:
    • Possibly overfitting (high variance)
    • Variance can be seen as the difference between the training error and the test error.
  • Aim for low training and test error (the ‘sweet spot’ - low bias and low variance).