Macro precision, recall and F1
Compare macro-averaged precision, recall and F1 for classification.
- Testing group
- Performance
- Applies to
- Classification
- App version
2.0.0- Channel
- stable
Required inputs
A model, task-compatible labelled evaluation data and the prediction settings used for the run.
Test procedure
Run the metric on the chosen evaluation split. Keep the task, label mapping, thresholds and aggregation settings with the result.
Interpreting results
Read the score against the task and the errors that matter. Inspect class or slice results before relying on a single aggregate.
Limitations
Evidence record
Retain predictions, reference labels, metric settings and the task-level result so comparisons use the same conditions.