Beginner · Evaluation

Precision

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. Of the items the model predicted positive, the fraction that are actually positive.

Technical Definition

Of the items the model predicted positive, the fraction that are actually positive.

How it works

Precision = TP / (TP + FP). High precision means few false alarms — important when acting on a positive prediction is costly (medical procedure, account ban). Always reported alongside recall, since you can trade one for the other.

Related Concepts

• Precision & Recall — Complementary metrics measuring classifier accuracy on positive predictions (precision) and ability to find all positives (recall).
• Recall — Of all the actually positive items, the fraction the model successfully found.
• F1 Score — The harmonic mean of precision and recall, balancing both into a single number.