Classification with univariate decision trees

We discuss how to classify data with a decision tree. This includes choosing the decision nodes so that the data "impurity" is decreased step-by-step, ultimately leading to "pure" leaf nodes where all datapoints reaching them belong to the same class. We discuss how to split a node based on both numerical and discrete features.