Much like when we are learning something new, this will begin with a careless, reckless, flawed (at least on some level) approach. I encourage the reader to seek ways of improving our models and code as we go on. Later, we may end up with very similar or different solutions. If you can't address an alternative at the time or even if your alternative doesn't go well, I guarantee that, by paying that much attention, you will learn more from the reading experience.
A great way to start is by discussing which R packages we could use to make trees, highlighting which features we could expect from each of them. Table 6.2 introduces briefly some packages used to estimate tree models, as well as popular features for each ...
