AI & Machine Learning · Foundational

Decision Tree

A model that predicts by learning a hierarchy of if-then splits on feature values.

Definition

Decision trees split data at each node on the feature and threshold that best separate the target, using criteria such as Gini impurity, entropy or variance reduction. They are interpretable and handle mixed data types without scaling, but single deep trees overfit easily. They are the building block for random forests and gradient boosting.

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