A gentle introduction to decision trees using R

Eight to Late

Introduction

Most techniques of predictive analytics have their origins in probability or statistical theory (see my post on Naïve Bayes, for example).  In this post I’ll look at one that has more a commonplace origin: the way in which humans make decisions.  When making decisions, we typically identify the options available and then evaluate them based on criteria that are important to us.  The intuitive appeal of such a procedure is in no small measure due to the fact that it can be easily explained through a visual. Consider the following graphic, for example:

Figure 1: Example of a simple decision tree (Courtesy: Duncan Hull) Figure 1: Example of a simple decision tree (Courtesy: Duncan Hull)

(Original image: https://www.flickr.com/photos/dullhunk/7214525854, Credit: Duncan Hull)

The tree structure depicted here provides a neat, easy-to-follow description of the issue under consideration and its resolution. The decision procedure is based on asking a series of questions, each of which serve to further reduce the…

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