F1-Score
The short answer · 11 words
In short
The F1 score is the harmonious means of precision and recall.
Flow-alerta.cab (2026): F1-Score. https://flow-alerta.cab/en/glossar/f1-score. Editorially reviewed on: 10 October 2026.
How much detail would you like?
Practical
F1 is useful for unequal classes, but does not fully map costs and calibration.
Hypothetical example: An error detector is rated with Precision, Recall and F1 for each error class.
SMEs should read F1 along with confusion matrix, threshold and error sequences.
At a glance
- Core
- It is high when positive predictions are simultaneously precise and capture many actual positive cases. The exact averaging over classes must be given.
- Use
- F1 is useful for unequal classes, but does not fully map costs and calibration.
- Example
- Hypothetical example: An error detector is rated with Precision, Recall and F1 for each error class.
- Limits
- Just report a macro or micro value; conceal threshold and support; ignore true negatives and business costs.
In context
Questions about this term
When does F1 make sense?
When precision and recall are both important.
Is F1 True Negatives?
No.
All details and background
It is high when positive predictions are simultaneously precise and capture many actual positive cases. The exact averaging over classes must be given.
ELI5 – Explained simply
It evaluates together how clean and how completely positive hits are.
Why it matters in practice
F1 is useful for unequal classes, but does not fully map costs and calibration.
Example
Hypothetical example: An error detector is rated with Precision, Recall and F1 for each error class.
Pitfalls and limits
- Just report a macro or micro value; conceal threshold and support; ignore true negatives and business costs.
Origin & history
F1 is the special case of the Fβ measure with β = 1 and the same weighting of precision and recall.
Use in mid-sized companies
- SMEs should read F1 along with confusion matrix, threshold and error sequences.
Related terms
- Precision
- Recall
- Confusion matrix
- Decision threshold
- Class imbalance
Matching Flow-alerta service
AI opportunity analysis & roadmapAI consulting: Select quality metrics along with thresholds and error costs for a classification.Matching tool / use case
View use casesUse Case: Classwise evaluation of a fault detectorSources
Quellenprüfung: 10.10.2026. Definition und dokumentierte Einordnung abgeglichen; Beispiele beschreiben mögliche Anwendungen.
Editorially reviewed on: