Decision Tree with Python
Introduction Last time we talked about non-linear classifier using Support Vector Machines or SVM . Today we'll be discussing another non-linear classifier and regressor called decision tree. The way decision tree works is by creating a model, which predicts the value of a target variable by learning simple decision rules inferred from the data features. Since trees can be visualized and is something we're all used to, decision trees can easily be explained, visualized and manipulated the non-linearity in an intuitive manner. Surely there are some disadvantages as well, but we'll note them a bit later, firstly let's see them in action. Implementation It won't come as a complete surprise to you, that scikit package has already taken initiative and implemented the whole thing using DecisionTreeRegressor and DecisionTreeClassifier classes. What is left for us is to bear the fruits of someone else's hard labour. import StringIO import numpy as np im