ROC AUC Calculator
Calculate the ROC curve point and estimated AUC from confusion matrix values. Understand your classifier's discrimination ability with this simple tool.
How to Use the ROC AUC Calculator
- Enter True Positives (TP).
- Enter True Negatives (TN).
- Enter False Positives (FP).
- Enter False Negatives (FN).
- Click Calculate to get TPR, FPR, and AUC.
Anwendungsfälle
- •Evaluating binary classifier discrimination performance.
- •Comparing multiple models at a given operating point.
- •Selecting classification thresholds for specific requirements.
- •Reporting model quality in medical and security applications.
Formel
TPR = TP/(TP+FN). FPR = FP/(FP+TN). AUC ≈ TPR×(1−FPR/2) — single-point trapezoidal approximation.
Häufig gestellte Fragen
What is AUC?
AUC (Area Under the ROC Curve) measures a classifier's ability to distinguish between classes. AUC of 1.0 is perfect; 0.5 is random.
What is TPR?
True Positive Rate (sensitivity/recall) = TP / (TP + FN).
What is FPR?
False Positive Rate (fall-out) = FP / (FP + TN), the rate of incorrectly classified negatives.