ISTQB Certified Tester: AI Testing Practice Mode

Community Discussion

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• Chose A0

  - On a 99/1 imbalanced dataset, a trivial model that always predicts the majority class achieves 99% accuracy while completely failing on the minority class. Accuracy hides this failure. Precision, recall, F1, and PR-AUC focus on positive-class performance and reveal the true behavior. ROC-AUC can also be misleading on heavy imbalance because it weights specificity equally with sensitivity.