Performance & Evaluation

F1 Score

A combined measure of precision and recall — the harmonic mean of both.

Definition

The F1 score combines precision and recall into a single metric, giving equal weight to both. It's particularly useful when you want to balance the two — avoiding both false alarms (low precision) and missed cases (low recall). An F1 score of 1.0 is perfect; 0.0 is completely wrong. It's a standard metric for classification tasks where neither precision nor recall alone tells the full story.

Related Terms

Precision

The proportion of the AI's positive predictions that are actually correct.

Recall

The proportion of actual positives that the model correctly identifies.

Accuracy

How often an AI produces correct outputs on a given task.

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Disclaimer

This definition is provided for educational and informational purposes only. It represents a general explanation of a technical concept and does not constitute professional, technical, or investment advice. Artificial intelligence is a rapidly evolving field; terminology, techniques, and capabilities change frequently. Coaley Peak Ltd makes no warranty as to the accuracy, completeness, or currency of the information provided. Nothing on this page should be relied upon as the sole basis for commercial, technical, legal, or investment decisions without independent professional advice.

Document reference: ISO_webpage_knowledge-base_glossary_v1

Last modified: 29 March 2026

Knowledge Base·Performance & Evaluation·F1 Score