Recall measures the proportion of the total possible true positive results that the model was able to identify.

 

Recall =                         true positives                   

                       true positives + false negatives

 

For example, for every 100 verbatims which should have been labelled as ‘Request for information’, the recall would be the percentage that the platform successfully found.

 

A 77% recall would mean that for every 100 verbatims that should have had a specific label predicted, there would be 23 verbatims which should have been predicted as having the label, but the platform missed them.

 

For a more detailed explanation on how recall works, please see here.

---

Previous: Precision     |     Next: Reviewed and unreviewed verbatims