AI engineering glossary · Evaluation metrics
What is calibration?
Calibration (also called probability calibration, model calibration): The property that a model's stated confidence matches how often it is actually right. A well-calibrated classifier that says 70% should be correct on about 70% of such predictions. It matters wherever probabilities feed decisions, such as risk pricing or triage.
Calibration: an example
Among 1,000 loan applicants each given a 20% default probability, roughly 200 should default if the model is calibrated.
Related terms
More Evaluation metrics terms
- Calinski-Harabasz index
- Catalogue coverage
- Character error rate
- chrF
- CIDEr
- Cohen's kappa
- Confusion matrix
- Continuous ranked probability score
Where you learn it
Calibration is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.