Which cross-validation approach is specifically recommended for tim…

Question

Which cross-validation approach is specifically recommended for time series data where the relationship between features and target evolves over time?

Accepted Answer

Walk-forward (rolling origin) cross-validation training only on past data and validating on future data — Here's the deal — c is correct because walk-forward CV respects temporal ordering — each fold trains on all data before the validation period and tests on subsequent data, preventing future information leakage. A (stratified k-fold) randomly shuffles data, destroying temporal structure.

Answer

Stratified k-fold cross-validation maintaining class proportions across folds

Answer

Leave-one-out cross-validation (LOOCV) to maximize training data per fold

Answer

Repeated k-fold cross-validation with multiple random seeds

Which cross-validation approach is specifically recommended for time series data where the relationship between features and target evolves over time?

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Full Explanation