In a fraud detection scenario where the problem is to predict if a transaction is fraud or not, a model provides predictions that correctly identify
In a fraud detection scenario where the problem is to predict if a transaction is fraud or not, a model provides predictions that correctly identify fraudulent transactions 94% of the time. Is this a good model? Yes, this model identifies fraud with a very high percentage. Not sure until we know about the false positive rate, ROC, or other metrics that capture the false positive rate as well. No, this is the incorrect evaluation metric to use. The ASE of the test set is more appropriate for this type of problem.
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