In regression problems, sometimes scaling the targets can save time and allow us to use simpler models for the problems at hand. In this section, we are going to see how to make our estimator's life easier by changing the scale of our targets.
In the following example, the relation between the target and the input is non-linear. Therefore, a linear model would not give the best results. We can either use a non-linear algorithm, transform our features, or transform our targets. Out of the three options, transforming the targets can be the easiest sometimes. Notice that we only have one feature here, but when dealing with a number of features, it makes sense to think of transforming your targets first.
The following plot shows the relation between a single feature, x, and a dependent variable, y:
Between you and me, the following code was used to generate data, but for the sake of learning...
