Now that we have created our model, we can reuse it in Tableau. This model will just work in Tableau, as long as you have Rserve running. You will also need to have the relevant packages installed, as per the script. In particular, the
rpart package is the workhorse of this example, and it must be installed since it is self-contained as it loads the library, trains the model, and then uses the model to make predictions within the same calculation.
There are many ways to deploy your model for future use, and this part of the process involves the CRISP-DM methodology. Here are a few ways:
You can go through the model fitting inside R using RStudio or another IDE and save it. Then, you could simply load the model into Tableau or you can save it to a file directly from within Tableau. The advantage of doing it in this way is that you can reuse your R model in other packages as well. The downside is that you will need to switch between R and Tableau, and then back again.