Data Classification with Decision Trees

In this chapter, we will develop the theory for binary decision trees. Decision trees can be used to classify data and fall into the Learning category in our Autonomous Learning taxonomy. Binary trees are easiest to implement because each node branches to two other nodes, or none. We will create functions for the decision trees and to generate sets of data to classify. Figure 10.1 shows a simple binary tree. Point “a” is in the upper-left quadrant. The first binary test finds that its x value is greater than one.