ROC Curve is a graphical plot used to evaluate the performance of a binary classification system. It plots the True Positive Rate (TPR) against the False Positive Rate (FPR) at various threshold settings.
Understanding the ROC Curve
The area under the ROC curve (AUC) is a measure of how well a parameter can distinguish between two diagnostic groups (diseased/normal). A higher AUC represents better performance. The ROC curve is widely used in medical decision making, radiology, and other areas.
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