Vocabulary

Understand the term. Connect the concept.

A practical dictionary of 512 AI, machine learning, mathematics, and programming terms from HerbDev’s AI Vocabulary app. Start with a definition, explore an example, then follow the concepts behind it.

Linked concepts open in a new tab. Audio reads the definition and example.

Recall

Model Evaluation · Level 2 of 5

Recall

The fraction of actual positives that the system identifies.

It asks how many relevant cases were found.

Example

A detector finds eight of twenty real defects.

Listen to the definition and example

Audio transcript

Recall. The fraction of actual positives that the system identifies. It asks how many relevant cases were found. For example: A detector finds eight of twenty real defects.

Explore this concept

A useful analogy

Of all the things you hoped to find, how many did you catch?

Why it matters

This helps you ask what a reported score counts and which errors it can hide.

Technical detail

Recall = TP / (TP + FN). With no actual positives, a reporting convention is needed.

Common misconception

High recall can coexist with many false alarms.

Start with

Related concepts

Quick recall question

Try answering before looking back at the definition.

Put the terminology into context: How AI works · Machine-native representations · All learning paths

Manage browser learning data

“Remove my test data” clears all AI 101 and ML 101 scores, reviews, project checklists and rating selections, plus saved vocabulary and recent history in this browser. Test entries cannot be separated from other learning progress. Cookie preferences, security protections, submitted feedback, contact emails and past analytics are kept.