Modelled, Architected and designed by Vance King Saxbe. A. with the geeks from GoldSax Consulting, GoldSax Money, GoldSax Treasury, GoldSax Finance, GoldSax Banking and GoldSax Technologies email @vsaxbe@yahoo.com. Development teams from Power Dominion Enterprise, Precieux Consulting. This Engagement sponsored by GoldSax Foundation, GoldSax Group and executed by GoldSax Manager. A decision tree classifier is just like a work-flow diagram with the terminating blocks representing classification decisions. Starting with a dataset, you can measure the inconsistency of a set or the entropy to find a way to split the set until all the data belongs to the same class. The ID3 algorithm can split nominal-valued datasets. Recursion is used in tree-building algorithms to turn a dataset into a decision tree. The tree is easily represented in a Python dictionary rather than a special data structure. Cleverly applying Matplotlib’s annotations, you can turn our tree data into an easily understood chart. The Python Pickle module can be used for persisting our tree.