On a ROC curve, the y-axis represents which metric?

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Multiple Choice

On a ROC curve, the y-axis represents which metric?

Explanation:
The y-axis shows sensitivity, the true positive rate—the proportion of actual positives correctly identified by the classifier. This is why the ROC curve maps how sensitivity changes as you vary the decision threshold. The horizontal axis is the false positive rate, which equals 1 minus specificity. Specificity and accuracy aren’t plotted as axes on the ROC curve, though they relate to the curve through threshold choice. The area under the curve (AUC) summarizes overall discrimination across thresholds.

The y-axis shows sensitivity, the true positive rate—the proportion of actual positives correctly identified by the classifier. This is why the ROC curve maps how sensitivity changes as you vary the decision threshold. The horizontal axis is the false positive rate, which equals 1 minus specificity. Specificity and accuracy aren’t plotted as axes on the ROC curve, though they relate to the curve through threshold choice. The area under the curve (AUC) summarizes overall discrimination across thresholds.

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