Intermediate
Artificial Intelligence & Machine Learning
Q54 / 100
What is the difference between precision-recall and ROC curves?
Correct! Well done.
Incorrect.
The correct answer is B) PR curves focus on positive class performance (better for imbalanced datasets); ROC curves show true vs false positive rates across all thresholds
B
Correct Answer
PR curves focus on positive class performance (better for imbalanced datasets); ROC curves show true vs false positive rates across all thresholds
Explanation
With severe class imbalance, ROC AUC can be misleadingly optimistic (many TN inflate FPR denominator). PR AUC focuses on the minority positive class. For fraud detection (rare events), PR is more informative.
Progress
54/100