Decision Tree (DT): A Valuable Tool for Water Resources Engineering

Abstract

AbstractOne way to choose the best option among several possible options when making a decision is to visualize the possible options. However, because each decision is made up of smaller decisions, decision-making can be a hierarchical and challenging process that may impact the decision maker’s ability to make the best decision in the shortest time. The Decision Tree (DT) approach is an effective tool in the hierarchical decision-making process that has been widely used in different fields of science and engineering. Because the DT hierarchical process helps to split a decision into details. That is a tree-like structure by which the smaller details and decisions that the decision-maker faces during the decision-making process become clearer. One of the most important features of DT is the “classification” ability, which is used in all sciences. In fact, DT is a way to break away from traditional classification in advanced ways. After classifying the data, DT curiously searches for the rules governing the data decision space. It should be noted, however, that DT can be used for both classification and regression problems, but is often used more in classification problems. It should be noted that this approach is one of the most effective tools in other fields such as text mining, information extraction, machine learning, and pattern recognition. In this chapter of the book, the differences between the use of DT in classification and regression issues, as well as the concepts and structure of DT, along with its application in MATLAB are presented.KeywordsDecision-makingMachine learningData miningDecision tree