AI engineering glossary · Evaluation metrics
What is precision-recall curve?
Precision-recall curve (also called PR curve): A plot of precision against recall as the decision threshold varies. It ignores true negatives, so it is more informative than the ROC curve when positives are rare. A curve that stays high toward the top-right indicates a model that finds most positives with few false alarms.
Precision-recall curve: an example
For a fraud model where only 2% of transactions are fraud, the team plots precision versus recall over thresholds to pick a setting that keeps precision above 0.5.
Related terms
More Evaluation metrics terms
- Precision-recall trade-off
- Prediction interval coverage
- Prevalence
- Proper scoring rule
- R-precision
- Recall
- Recall at k
- Reciprocal rank
Where you learn it
Precision-recall curve is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.