Decision Trees are a predictive modeling technique that generates rules that derive the likelihood of a certain outcome based on the likelihood of the preceding outcomes. In general, decision trees are typically constructed similar to a flowchart, with a series of nodes and leaves that denote a parent-child relationship. Nodes that do not link to other nodes are known as leaves.
Decision Trees belong to a class of algorithms that are often known as CART (Classification and Regression Trees). If the outcome of interest is a categorical variable, it falls under a classification exercise, whereas if the outcome is a number, it is known as a regression tree.
An example will help to make this concept clearer. Take a look at the ...
