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Communications Mining User Guide
Last updated Nov 7, 2024

Recall

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 messages which should have been annotated as ‘Request for information’, the recall would be the percentage that the platform successfully found.

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

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

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