What is pruning in decision trees and why is it important?

Pruning removes unnecessary branches in a decision tree to reduce overfitting.

Pruning simplifies a decision tree by cutting branches that provide little predictive power. Pre-pruning stops growth early using constraints, while post-pruning removes branches after full training. This improves generalization and reduces model complexity.