What is decision tree learning?

Decision tree learning is a supervised machine learning approach used to predict the value of a target variable by learning simple decision rules inferred from the data features. It works by recursively partitioning the data into subsets based on the values of input features, ultimately leading to a tree-like structure that can be used for classification or regression tasks. Commonly used in various fields like finance, healthcare, and marketing for tasks like credit risk assessment, disease diagnosis, and customer segmentation.