Decision Tree Prunning: Revision history

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    5 November 2024

    • curprev 07:1007:10, 5 November 2024‎ 핵톤 talk contribs‎ 4,593 bytes +4,593‎ Created page with "Pruning is a technique used in decision trees and machine learning to reduce the complexity of a model by removing sections of the tree that provide little predictive power. The primary goal of pruning is to prevent overfitting, ensuring that the model generalizes well to unseen data. Pruning is widely used in decision trees and ensemble methods, such as random forests, to create simpler, more interpretable models. ==Types of Pruning== There are two main types of pruning..." Tag: Visual edit
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