In your online business, you may want to estimate the lifetime value of your users in the next month, the next quarter, and the next year. You could build three different regressors for each one of these three separate estimations. However, when the three estimations use the exact same features, it becomes more practical to build one regressor with three outputs. In the next section, we are going to see how to build a multi-output regressor, then we will learn how to inject interdependencies between those estimations using regression chains.
Building a multi-output regressor
Some regressors allow us to predict multiple targets at once. For example, the ridge regressor allows for a two-dimensional target to be given. In other words, rather than having y as a single-dimensional array, it can be given as a matrix, where each column represents a different target. For the other regressors where only single targets are allowed...
