It is sometimes useful to be able to convert a decision tree into an actual useful code snippet. This notebook shows how you’d go around to achieve this.
We will use as an example, the iris dataset (which is a toy example and not really that interesting but sufficiently interesting that we can show a usable final result and make a point).
We will take the dataset, split it into training set and testing set (70%/15%) and we will train a minimal DecisionTree over it.
With the above trained decision tree we can convert it into actual python code.