The Importance of Time-Based Cyclic Features and Lag Features for Time Series Data - ÄLLITÄ article

Time series data is an essential component in various fields including finance, economics, energy, weather forecasting, and many more. It is important to include lag features and time-based cyclic features to extract meaningful insights from the data and to improve forecasting accuracy. These features enhance the performance of AI/ML models by capturing underlying patterns and dependencies in time series data.