Pruning In Decision Tree (1) What Is Pruning? Pruning is a technique used in decision trees to reduce overfitting and improve the generalization ability of the model. It involves removing branches or nodes from the tree that do not contribute significantly to its predictive accuracy. Pruning helps simplify the tree structure, making it less complex and easier to interpret. There are two main types of pruning techniques: (2) Types Of Pruning. Pre Pruning: Pre-pruning involves stopping the growth of the decision tree before it becomes fully expanded. It applies stopping criteria during the construction process to determine when to stop

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