Classification Metrics (Accuracy, Precision, Recall, F1)

Summary

Accuracy alone is misleading on imbalanced data — precision measures how many predicted positives were correct, recall measures how many actual positives were caught, and F1 balances both.

• 1Calculate all 4 metrics by hand on a small confusion matrix example.
• 2Learn a scenario where you'd prioritize recall over precision (e.g. cancer screening) and vice versa.
• 3Practice choosing the right metric for a given business problem before training a model.