Imbalanced Datasets in Production

Accuracy is always the best metric for any classification problem A naive model predicting the majority class achieves 99.9% accuracy, making it misleading; precision-recall metrics or AUC-PR better capture performance on the rare class Accuracy is wrong because it cannot be computed on binary classification Accuracy penalizes the model too heavily for missing fraud cases