Key Facts:

  • Nothing to do with training. It is in fact a way of evaluating the trained class
  • Made by running the trained classifier on validation or test set.
  • Horizontal Axis = False Positive Rate.
  • Vertical Axis = True Positive Rate (Sensitivity).
  • ROC Curve is discrete.
  • The area under the curve determines
  • Random Classifier will have an area of 0.5
  • The Knob is not in the diagram*

Important: In practice, the trade-off between false negatives and false positives is usually negotiated by choosing a point on this plot, based on real test data.