65. ROC Curves and AUC: Comparing Models Fairly

You have two models. Model A has F1 of 0.82. Model B has F1 of 0.79. Model A wins, right? Not necessarily. F1 is calculated at one specific threshold. Maybe Model B is much better at other thresholds. Maybe on your actual deployment threshold, B beats A. ROC curves show you the full picture. They plot model performance across every possible threshold at once. AUC collapses that into one number you can compare. It's the right way to compare classifiers when you haven't committed to a threshold ye