You're trying to compare two classification models, and they have the same AUC value but different ROC Curves. What does this tell you, and how would you choose between the models?
- The models are identical in performance
- The models perform equally overall but may have different trade-offs at specific thresholds
- The models perform equally well on positive classes but differently on negative classes
- nan
Same AUC value means the models perform equally overall, but different ROC Curves indicate that they may have different trade-offs at specific thresholds. The choice between models should depend on the specific needs and priorities of the application.
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