A ferry no-show score will be cut at different operating points depending on how full the lot is. A single 0.5 accuracy is not enough. Which evaluation pair compares ranking quality across thresholds?
Select an answer to reveal the explanation.
Short Explanation
The ferry no-show cut will move with lot fullness. A ROC curve and AUC compare ranking across those thresholds. A single 0.5 accuracy is one snapshot, Translate is not a ROC, and RMSE is a regression error.
Full Explanation
A ROC curve and AUC summarize ranking quality across thresholds when the operating point will move. A single 0.5 accuracy does not. Translate is not a ROC display, and RMSE is a regression error.