AI engineering glossary · Evaluation metrics
What is brier score?
Brier score: The mean squared difference between predicted probabilities and the actual 0/1 outcomes: (1/N) * sum of (p - y)^2. It ranges from 0 to 1 for binary events, lower is better, and it rewards predictions that are both accurate and well calibrated. It is a proper scoring rule.
Brier score: an example
A forecaster says 80% chance of rain and it rains (y = 1): the squared error is (0.8 - 1)^2 = 0.04.
Related terms
More Evaluation metrics terms
- Calibration
- Calinski-Harabasz index
- Catalogue coverage
- Character error rate
- chrF
- CIDEr
- Cohen's kappa
- Confusion matrix
Where you learn it
Brier score is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.