Stop 11 · Time Series AnalysisTopics · 6/7
Time Series Cross-Validation
Part of the Data Science Roadmap
In short
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.
How to learn this
- 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.
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