What are precision and recall curves in machine learning?

What are precision and recall curves in machine learning?

Precision and recall curves are graphical representations that help evaluate the performance of a classification model.

How do I interpret these curves?

The precision-recall curve plots precision against recall for different thresholds, helping you understand trade-offs.

What does a high precision and low recall indicate?

It indicates that while the model is accurate when it predicts a positive class, it misses many actual positives.

Can you give an example of when to use these curves?

They are particularly useful in imbalanced datasets where one class is more important than the other.