https://nalar.dev/tags/time-series/ Recent content in Time Series on Nalar Hugo en-us Tue, 01 Sep 2026 00:00:00 +0700 https://nalar.dev/time-series-cross-validation-with-walk-forward-splits/ Tue, 01 Sep 2026 00:00:00 +0700 https://nalar.dev/time-series-cross-validation-with-walk-forward-splits/ <p>Random train/test splits assume examples are exchangeable. Time-series data violates that assumption because the future occurs after the past, and production models normally predict observations that were not available during training.</p> <p>Walk-forward validation preserves that chronology.</p> <h2 id="why-random-splitting-is-misleading">Why random splitting is misleading</h2> <p>Suppose you want to predict next week&rsquo;s demand from historical sales. A random split can place March observations in the test set while April observations appear in training.</p> <p>Even if features do not explicitly contain future values, the evaluation now uses a model fitted on a future regime. Seasonality, pricing, inventory, customer behavior, and economic conditions can all make the score more optimistic than deployment reality.</p>