What are precision and recall?

02 · See it in action

Follow the steps

1. Build a confusion matrix with true and false positives.
2. Calculate precision using predicted positives as the denominator.
3. Calculate recall using actual positives as the denominator.
4. Compare thresholds on validation examples before selecting one.

Worked example

True positives = 8, false positives = 2, false negatives = 4
Precision = 8 / (8 + 2) = 0.80
Recall = 8 / (8 + 4) = 0.667
F1 = 2 * precision * recall / (precision + recall) ≈ 0.727

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