What is the difference between precision and recall, and when would you prioritize recall over precision?

Question

Machine Learning — Medium

What is the difference between precision and recall, and when would you prioritize recall over precision?

Accepted Answer

Precision and recall are both metrics used to evaluate the performance of a machine learning model. Precision measures the proportion of true positive predictions among all positive predictions, while recall measures the proportion of true positive predictions among all actual positives. Recall is prioritized over precision when missing a positive case, like a cancer diagnosis or fraud detection, can have severe consequences.