In this blog I'll address the CART tree sequence. CART follows a forward growing and a background pruning process to arrive at the optimal tree. In the process CART generates for us, not just one model, but a collection of progressively simpler models. This collection of models is known as the "tree sequence." In this article I will explain the forward and backwards tree generation process. I will also discuss how a modeler might use judgment to select a near optimal tree that might be better for deployment than the so–called optimal tree. (this blog is a transcript of the video below).
To illustrate this example, I'll use the "euro telco mini" excel file.
- Set up the model, and make sure to select a dependent variable. (Exclude the record ID, which we don't want in the model and indicate the city and the marital status are categorical variables now hit the start button)