Objectives:

The objectives of this section are:
to introduce you to the various attribute types and the ways they can be split
to present you with an algorithm for creating a decision tree classifier
to determine the best split for a given node
to inform you of the problems that arise with the algorithm and how they are addressed.

Outcomes:

By the time you have completed this section you will be able to:
compare decision trees and decide whether or not they are efficient
explain from a high level Hunts’ algorithms and the difficulties encountered
calculate the impurity of a node by using the measures outlined in this section
compare and contrast the measures of impurity