José Hernandez-Orallo, Peter Flach and Cèsar Ferri

- A curve to graphically understand and assess classifiers
- We assume that the classifier scores are posterior class probabilities
- This provides a natural way of choosing the thresholds
- This new curve depends on the quality of the probability estimates
- It shows the performance for the full range of operating conditions
- We can choose and discard classifiers depending on the operating conditions
- We can also combine classifiers in order to obtain a lower overall loss
- The area under the Brier curve for cost proportions is equal to the Brier score
- Complete details in the ICML'11 paper.
- An R script for drawing Brier cuves.