What are the key metrics derived from a confusion matrix?

What are the key metrics derived from a confusion matrix?

The key metrics include accuracy, precision, recall, F1 score, and specificity. Would you like to know how to calculate them?

Yes, please explain how to 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.

What do these metrics tell us about model performance?

Precision indicates the quality of positive predictions, while recall shows how well the model identifies actual positives. Both are crucial for understanding model effectiveness.

Can you give an example of when to prioritize precision over recall?

Certainly! In medical diagnosis, prioritizing precision is vital to avoid false positives, which could lead to unnecessary treatments.