Python: Real-World Data Science

Decision trees

Decision trees are a class of supervised learning algorithm like a flow chart that consists of a sequence of nodes, where the values for a sample are used to make a decision on the next node to go to.

As with most classification algorithms, there are two components:

• The first is the training stage, where a tree is built using training data. While the nearest neighbor algorithm from the previous chapter did not have a training phase, it is needed for decision trees. In this way, the nearest neighbor algorithm is a lazy learner, only doing any work when it needs to make a prediction. In contrast, decision trees, like most classification ...