Why is standard k-fold cross-validation wrong for time series?
- A Random splitting trains on future data to predict the past
- B Time series cannot be split
- C Folds would be unequal
- D It requires too much memory
Answer
Random splitting trains on future data to predict the past
Forward-chaining validation reflects how the model will actually be used, training only on data available before the prediction point.





