Statistics

Confusion Matrix Calculator

Find accuracy, precision, recall and F1 from a confusion matrix.

Parameters Live Compute
Calculated Output
Precision 0.8889
Recall 0.8
F1 score 0.8421
Accuracy 0.85
Formula: precision = TP/(TP+FP); recall = TP/(TP+FN)
Step-by-Step Breakdown
1. Values used:
2. True positives = 80
3. False positives = 10
4. False negatives = 20
5. True negatives = 90
6.
7. Precision = 0.8889
8. Recall = 0.8
9. F1 score = 0.8421
10. Accuracy = 0.85
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The confusion matrix summarizes a classifier's correct and incorrect predictions.

The math behind it

Precision = TP/(TP+FP), recall = TP/(TP+FN), F1 is their harmonic mean.

Worked Example

TP 80, FP 10, FN 20 → precision 0.89, recall 0.80, F1 0.84.

Frequently Asked Questions

Precision vs recall?

Precision is how many predicted positives are real; recall is how many real positives you caught.

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