Time Series Cross-Validation

Summary

Standard k-fold cross-validation doesn't work for time series (it would leak future data into training) — instead, you use expanding or rolling windows that always train on the past and validate on the future.

• 1Implement a rolling-window cross-validation split on a sample time series.
• 2Learn why randomly shuffling time series data before splitting is a critical mistake.
• 3Compare model performance across multiple rolling windows, not just a single split.