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A fraud detection dataset contains 1% fraud cases and 99% non-fraud cases. Which...

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A fraud detection dataset contains 1% fraud cases and 99% non-fraud cases. Which approach is most appropriate to consider?

Use accuracy only and ignore the minority class.

0%

Train only on the test set.

0%

Delete all fraud cases because they are rare.

0%

Use class weights, resampling, SMOTE, and metrics such as precision, recall, F1, or ROC-AUC.

100%

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