Decision tree (DT) is a statistical model that is used in classification. This machine-learning approach is used to classify data into classes and to represent the results in a flowchart, such as a tree structure . This model classifies data in a dataset by flowing through a query structure from the root until it reaches the leaf, which represents one class. The root represents the attribute that plays a main role in classification, and the leaf represents the class. The DT model follows the steps outlined below in classifying data:
It puts all training examples to a root.
It divides training examples based on selected attributes.
It selects attributes by using some statistical measures.