Data Science and Statistics

Recall, explained

Recall measures how many actual positives a model successfully finds.
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Part of the Semantic Notion technical glossary.

Short Definition

Recall measures how many actual positives a model successfully finds.

Intuition

Recall asks: out of everything we needed to catch, how much did we catch?

Technical Definition

Recall is true positives divided by true positives plus false negatives.

Example

In cancer screening, high recall means fewer true cases are missed.

Common Misunderstandings

Recall does not measure how many positive predictions were false alarms.
High recall can come at the cost of lower precision.

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