ROC Curve Comparison

Understanding ROC Curves

ROC (Receiver Operating Characteristic) curve plots True Positive Rate (TPR) vs False Positive Rate (FPR) at various thresholds.

AUC (Area Under Curve) measures overall classifier performance:

• AUC = 1.0: Perfect classifier
• AUC = 0.9-1.0: Excellent
• AUC = 0.8-0.9: Good
• AUC = 0.7-0.8: Fair
• AUC = 0.5-0.7: Poor
• AUC = 0.5: Random guessing (diagonal line)

TPR (Recall) = TP / (TP + FN) - How many actual positives we catch

FPR = FP / (FP + TN) - How many negatives we wrongly call positive