Glossary term

Recall

Of all the truly positive items, the share a model found.

How it works

Recall asks: of all the truly positive cases, how many did the model find? It equals true positives divided by true positives plus false negatives. High recall means few misses.

Recall looks at the 'actually positive' row

	Predicted positive	Predicted negative
Actually positive	True positive	False negative
Actually negative	False positive	True negative

In code

Recall

recall = tp / (tp + fn)

Why it matters

Recall matters when missing a case is costly, like failing to detect a disease.

Related terms

Precision F1 score Confusion matrix