In what scenario would the AUC be a more informative metric than simply using Accuracy?
- When the class distribution is balanced
- When the class distribution is imbalanced
- When the model has only one class
- nan
The AUC (Area Under the Curve) of the ROC Curve can be more informative than Accuracy when dealing with imbalanced class distribution. It provides a more holistic measure of the model's ability to discriminate between positive and negative classes, unlike Accuracy, which may be skewed.
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