Decision Tree Algorithm

The decision tree algorithm performs classifications based on a sequence that resembles a tree-like structure. It works by dividing the dataset into small subsets that serve as guides to develop the decision tree nodes. The nodes can be either decision nodes or leaf nodes, where the former represents a question or decision, and the latter represents the decisions made or the final outcome.

How Does It Work?

Considering this, decision trees continually split the dataset according to the parameters defined in the decision nodes. Decision nodes have branches coming out of them, where each decision node can have two or more branches. The branches represent the different possible answers that define the way in which the data is split.

Take, for instance, the following table, which shows whether a person has a pending student loan based on their age, highest education, and current income:

Figure 4.7: Dataset for student loans

A possible configuration of a decision tree built...