Interactive Confusion Matrix Explorer

Example: True Positives: True Negatives: False Positives: False Negatives:

Accuracy

0.875

Precision

0.895

Recall (Sensitivity)

0.850

F1 Score

0.872

Specificity

0.900

False Positive Rate

0.100

Accuracy = (TP + TN) / (TP + TN + FP + FN)

Precision = TP / (TP + FP) - Of all positive predictions, how many were correct?

Recall = TP / (TP + FN) - Of all actual positives, how many did we find?

F1 Score = 2 × (Precision × Recall) / (Precision + Recall)