AI engineering glossary · Evaluation metrics
What is F1 (f1 score)?
F1 score (also called F1, F-measure, F1-measure): The harmonic mean of precision and recall: F1 = 2 * precision * recall / (precision + recall). Because a harmonic mean is dominated by the smaller number, it is high only when both precision and recall are decent. It gives a single figure for imbalanced classification where accuracy is unhelpful.
F1 score: an example
With precision 0.60 and recall 0.75, F1 = 2 * 0.60 * 0.75 / 1.35, about 0.667.
Related terms
More Evaluation metrics terms
- False negative
- False negative rate
- False positive
- False positive rate
- Fleiss' kappa
- G-mean
- Gini coefficient
- Hamming loss
Where you learn it
F1 score is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.