# FAQ: Accuracy, Recall, Precision, and F1 Score - Recall

This community-built FAQ covers the “Recall” exercise from the lesson “Accuracy, Recall, Precision, and F1 Score”.

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This exercise can be found in the following Codecademy content:

## FAQs on the exercise Recall

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I can’t catch the meaning of describing this topic recall. What does it mean?

Our algorithm that always predicts `False` might have a very high accuracy, but it never will find any True Positives, so its recall is `0` . This makes sense; recall should be very low for such an absurd classifier.

Why "it never will find any True Positives, so its recall is `0` " ?

The result is 0 because 0 divided by any number is always 0. If there are no True Positives generated by the model the accuracy of the prediction will be 0.

That is what I understood of the exercise.