Why multi-step forecasting?
A multi-step forecasting task consists of forecasting the next H timesteps, yt+1,…, yt+H, of a time series, y1, …, yt, where H > 1. Most real-world applications of time series forecasting demand multi-step forecasting, whether it is the energy consumption of a household or the sales of a product. This is because forecasts are never created to know what will happen in the future but, rather, to enable us to take action using the visibility we get.
To effectively take any action, we would want to know the forecast a little ahead of time. For instance, the dataset we have used throughout the book is about the energy consumption of households, logged every half an hour. If the energy provider wants to plan its energy production to meet customer demand, the next half an hour doesn’t help at all. Similarly, if we look at the retail scenario, where we want to forecast the sales of a product, we will want to forecast a few days ahead...
