What is the difference between precision and recall in AI?

What is the difference between precision and recall in AI?

Precision measures the accuracy of positive predictions, while recall measures the ability to find all relevant instances.

Can you give examples of how precision and recall are used in different domains?

Sure! In medical diagnosis, high recall is crucial to identify all patients with a disease, while precision is important in spam detection to avoid false positives.

How do you calculate precision and recall?

Precision is calculated as true positives divided by the sum of true positives and false positives. Recall is true positives divided by the sum of true positives and false negatives.

Why is there often a trade-off between precision and recall?

There's a trade-off because increasing precision often reduces recall and vice versa. It depends on the specific application and its requirements.