Let's use what we have learned to create a model that can estimate the share counts for a given piece of content. We'll use the features we have already created, along with a number of additional ones.
Ideally, we would have a much larger sample of content—especially content that had more typical share counts—but we'll have to make do with what we have here.
We're going to be using an algorithm called random forest regression. In previous chapters, we looked at a more typical implementation of random forests that is based on classification, but here we're going to attempt to predict the share counts. We could consolidate our share classes into ranges, but it is preferable to use regression when dealing with continuous variables, which is what we're working with here.
To begin, we'll create...
