Decision trees can be categorized into various types based on their characteristics and purposes. Some common types include binary decision trees, multi-output decision trees, regression trees, classification trees, and random forests. Each type has its unique features and applications, catering to different problem domains.

Applications of Decision Trees

Decision trees have found relevance in a wide range of applications. In finance, they are used for credit scoring and investment analysis. In medicine, decision trees aid in diagnosing diseases and predicting patient outcomes. In customer relationship management, decision trees help with customer segmentation and churn prediction. Other domains, such as marketing, manufacturing, and fraud detection, also benefit from the applications of decision trees.

Decision Trees in Machine Learning