Welcome to the second part of the forester blog. In the previous part, we explained the main idea of the forester package, the motivations behind it, its advantages, and the innovations it brings to the ML world. You should definitely check it out! In this part, however, we will focus on showing the wide range of possibilities of the forester package and things you can achieve with it. We will present you the main functions of the package with their parameters and show how you can use them in your problems.

We discussed each step in the previous part using the graph below. Now we will try to explain how our package exactly works and what happens between the first and the last step of the process. The basic scheme of functions of our package is presented on the graph below. The only thing user has to do to create a model is to run one function. Then the data preprocessing is performed.