What are precision and recall in AI systems?

What are precision and recall in AI systems?

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

Can you give me an example of how precision and recall are used?

Sure! In a spam detection system, precision indicates how many of the flagged emails are actually spam, while recall shows how many spam emails were correctly identified.

Why are both metrics important?

Both metrics are crucial because they provide a balanced view of a model's performance, helping to avoid false positives and negatives.

How can I improve precision and recall in my model?

You can improve them by tuning your model's thresholds, using better features, or employing techniques like cross-validation.