Must-Know Base Tips for Feature Engineering With Time Series Data
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This article covers vital time series feature engineering techniques, complete with formulas and code examples. Learn to harness date/time features, domain-specific features, lag features, rolling/expanding windows, exponential smoothing (e.g., Holt-Winters), and seasonal decomposition (e.g., STL) to boost your machine learning model's predictive accuracy.