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 out of all emails marked as spam. Recall is the percentage of actual spam emails that were correctly identified.

Why is it important to consider both precision and recall?

Considering both helps balance the trade-off between false positives and false negatives, ensuring better model performance.

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

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