A decision tree is a machine learning algorithm that represents the inputs and outcomes in the form of a tree. They are used for building both classification and regression models. The decision tree contains nodes and edges which represent the events and decisions respectively. The first node is called the root node and branches into internal nodes. The final output node is called a leaf node. The leaf node represents the decision of the model. To download the cheatsheet, login below and subscribe to our YouTube channel.