Explain Decision tree

Decision trees use a tree-like structured algorithm which contains conditional control statements to predict the outcome based on the possible consequences. They are helpful in Machine learning specifically in decision analysis to help identify a strategy.

It uses an internal node that represents test in the attribute and a branch which represents the outcome of the test. It also contains leaf nodes that represent a class label and the entire process represents the rules of classification. The following diagram shows how a decision tree works