Decision trees are algorithms which again belong to the supervised machine learning algorithms family. They are also used for both classification and regression, often called CART, which stands for classification and regression trees. These are used a lot in decision support systems, business intelligence, and operations research.
Decision trees are mainly used for making decisions that would be most useful in reaching some objective and designing a strategy based on these decisions. At the core, a decision tree is just a flowchart with several nodes and conditional edges. Each non-leaf node represents a conditional test on one of the features and each edge represents an outcome of the test. Each leaf node represents a class label where predictions are made for the final outcome. Paths from the root to all the leaf nodes give us all the classification rules. Decision trees are easy to represent, construct, and understand. However, the drawback is that they are...