In a ROC curve, which axes correspond to the True Positive Rate and False Positive Rate?

• A. Precision on Y-axis and Recall on X-axis
• B. Accuracy on Y-axis and Error rate on X-axis
• C. True Positive Rate on Y-axis and False Positive Rate on X-axis
• D. Specificity on Y-axis and NPV on X-axis

Answer: (C)

In ROC curves, the vertical axis represents the True Positive Rate (also called sensitivity or recall), and the horizontal axis represents the False Positive Rate. This setup shows how increasing the threshold to label something as positive affects both how many true positives you catch and how many false positives you incur. The correct mapping—TPR on the Y-axis and FPR on the X-axis—accurately captures that trade-off across different thresholds. The other metrics listed (like precision/recall, accuracy/error rate, or specificity/NPV) are not the standard axes of a ROC plot (though FPR is related to specificity, since FPR = 1 − specificity).