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Decision trees are a popular type of machine learning model that are known for their simplicity and interpretability. They use a hierarchical structure of nodes and branches to make predictions based on splitting criteria and stopping criteria. Pruning is also used to prevent overfitting and create simpler, more interpretable trees.