What is the difference between precision and recall?

What is the difference between precision and recall?

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

Can you give me an example of precision and recall in a real-world scenario?

Sure! In email filtering, precision is the percentage of correctly identified spam emails, while recall is the percentage of actual spam emails that were correctly identified.

Why is it important to balance precision and recall?

Balancing precision and recall is crucial because high precision may lead to low recall and vice versa, affecting overall performance.

How can I improve both precision and recall in my model?

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