What is CART?

CART stands for Classification and Regression Trees. It is a decision tree learning technique used in machine learning and statistics. It is used for predictive modeling; constructing decision rules inferred from data to predict the value of a target variable. CART models are typically used for classification problems, where the goal is to predict the class to which a data point belongs, or regression problems, where the goal is to predict a continuous value. The trees are built by recursively partitioning the data based on the values of the input features, aiming to create homogeneous subsets with respect to the target variable. The technique is valuable for its interpretability and ability to handle both categorical and numerical data.