Training an AutoML forecasting model
Training an AutoML forecasting is most similar to training an AutoML regression model. Like regression and unlike classification, you are trying to predict a number. Unlike regression, this number is always in the future based on patterns found in the past. Also, unlike regression, you can predict a whole series of numbers into the future. For example, you can choose to predict one month out into the future or you can choose to predict 6, 12, 18, or even 24 months out.
Important tip
The further out you try to predict, the less accurate your forecasting model will be.
Follow the same steps you have seen in Chapter 4, Building an AutoML Regression Solution, and Chapter 5, Building an AutoML Classification Solution. First, begin by setting a name for your experiment. Then, set your target column and your AutoML configurations.
For forecasting, there is an additional step: setting your forecasting parameters. This is where you will set things...
