What is time-based feature engineering in time series data?

Time-based feature engineering extracts meaningful patterns from timestamps like trends, seasonality, and lags.

Time series feature engineering transforms raw timestamps into features such as day of week, rolling averages, lag features, and seasonal indicators. These features help models capture temporal dependencies and trends.