Answers for "model's precision and recall."

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model's precision and recall.

Precision quantifies the number of positive class predictions that actually belong to the positive class. Recall quantifies the number of positive class predictions made out of all positive examples in the dataset. F-Measure provides a single score that balances both the concerns of precision and recall in one number.

Posted by: Guest on March-15-2021

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