AI engineering glossary · Evaluation metrics
What is precision-recall trade-off?
Precision-recall trade-off (also called precision recall tradeoff): The tendency for precision and recall to move in opposite directions as the decision threshold changes. Lowering the threshold catches more true cases, raising recall, but also admits more false alarms, lowering precision. Choosing the threshold means deciding which error is more acceptable.
Precision-recall trade-off: an example
A resume-screening model set to shortlist anyone scoring above 0.3 finds nearly all suitable candidates but shortlists many unsuitable ones; raising the cut-off to 0.7 gives a cleaner list that misses more good people.
Related terms
More Evaluation metrics terms
- Prediction interval coverage
- Prevalence
- Proper scoring rule
- R-precision
- Recall
- Recall at k
- Reciprocal rank
- Relevance judgments
Where you learn it
Precision-recall trade-off is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.