ISTQB Certified Tester: AI Testing Practice Mode

Community Discussion

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• Chose B0

  - ROC-AUC is the area under the ROC curve, which plots true positive rate against false positive rate across all decision thresholds. It measures how well the model ranks positive examples above negative ones, independent of any specific threshold. A value of 0.5 is random; 1.0 is perfect ranking. PR-AUC is the area under the precision-recall curve and is preferred for imbalanced data.