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There is an imbalance in product distribution across stores, and I want to emphasize detection performance for the minority class. Which evaluation metric is most appropriate?
①Simple accuracy over all samples (accuracy)
②Compare only the cross-entropy loss values during training.
③The F1 score that indicates the balance between precision and recall, or the area under the precision–recall curve.
④Compare only based on training time and model size.
⑤Evaluate only the main diagonal elements of the confusion matrix.