CART, or Classification and Regression Trees, is a decision tree learning technique used for both classification and regression tasks. It works by recursively splitting the dataset into subsets based on feature values, creating a tree-like model that predicts outcomes. The strength of CART lies in its ability to handle both categorical and continuous data effectively while also providing clear interpretability through its visual structure.
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