Decision trees take parameters of a model and organize them into a tree structure, so one use the outputs of each parameter to make a decision. Decision trees to do not have to be binary, so they can have multiple decisions per node. When a leaf node is reached, this will output a final classification. Thus, decision trees are especially useful for classification and regression problems.

Defining the Model

Entropy and Information Gain

Building the Decision Tree

Regression Trees