Decision Tree Implementation in Python

January 30, 2014

Decision trees are an amzingly simple way to model data classification. This is an implementation of a ID3/C4.5 hybrid algorithm. The basic idea behind the model is to recursively cut the available data into two parts, maximizing information gain on each iteration.

Built for professor Doug Downey’s Machine Learning course at Northwestern University. More info on the assignment can be found here.

This was one of the first complex CS projects I worked on, which is evident by reading my sloppy code. You can find the implemantation here.

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