Explain the difference between Precision and Recall.

Explain the difference between Precision and Recall.

Approach: Define metrics using true positives, false positives, and false negatives.

Precision is the ratio of true positives to all predicted positives (quality). Recall is the ratio of true positives to all actual positives (quantity). Precision = TP / (TP + FP); Recall = TP / (TP + FN).

Follow-up: What is the F1-score?

Key concepts: confusion matrix, type I error, type II error.