PMLE Question 76

Community Discussion

Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.

• Chose B2

  Both random cross-validation and k-folds cross-validation are not suitable for time series data as those two can introduce data leakage leading to biased estimates/predictions. Nested cross-validation works with time series data avoiding data leakage and model overfitting

• Chose C1

  C, see desertlotus1211

• Chose C3

  You are working with time series data yet used random cross-validation, and you immediately achieved an extremely high AUC (99%) with little effort. This is a red flag for data leakage—meaning information from the future (or directly from the target) is leaking into the training process C is better answer