Decision Tree

The breakdown of this ID3 implementation would be something like this:
-> Make a table with given data
--> Calculate total entropy
--> Identify all the branches of each feature and calculate feature entropy
--> Pick the feature with the highest info gain
--> Do a divide and conquer, make child tables where feature column will have each branch of it at a time
--> Time for recursion, put these child tables inside the old process
--> Keep checking for absolute harmony in a branch!

The tree for the famous "PlayGolf/Tennis" example generated by this code is quite close compared to the tree of the example:p