A data scientist is comparing two binary classification models, Model A and Model B, for a credit default prediction task. Model A achieves an Area Under the Curve (AUC) of 0.85, while Model B achieves an AUC of 0.82. A detailed analysis of their Receiver Operating Characteristic (ROC) curves reveals that Model B's curve is positioned above Model A's curve for all False Positive Rate (FPR) values below 0.2. Conversely, Model A's curve is superior for all FPR values above 0.2. The primary business requirement is to select a model that performs best while maintaining a very low rate of incorrectly flagging creditworthy customers as high-risk, specifically keeping the FPR under 0.2. Given this constraint, which model should be recommended and why?
Model A, because its overall Area Under the Curve (AUC) is higher, indicating superior performance across all classification thresholds.
Model B, because it has a higher True Positive Rate (TPR) for the acceptable range of False Positive Rate (FPR) defined by the business constraint.
Neither model, as a different metric like Precision-Recall AUC should be used since the AUC values are too close to make a definitive decision.
Model A, because a higher AUC guarantees a lower number of total misclassifications regardless of the chosen threshold.
The correct answer is to select Model B. The Receiver Operating Characteristic (ROC) curve plots the True Positive Rate (TPR) against the False Positive Rate (FPR) at various classification thresholds. The Area Under the Curve (AUC) provides an aggregate measure of a model's performance across all possible thresholds. While Model A has a higher overall AUC, this metric can be misleading if the business requirements prioritize performance within a specific range of the curve. In this scenario, the business has a strict requirement to keep the FPR below 0.2. The problem states that Model B's ROC curve is above Model A's in this specific region (FPR < 0.2). A higher position on the ROC curve indicates a higher TPR for a given FPR, signifying better performance. Therefore, despite its lower overall AUC, Model B is the superior choice because it better satisfies the specific business constraint by providing a higher TPR within the acceptable FPR range.
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