How can I prevent overfitting in decision trees?

How can I prevent overfitting in decision trees?

To prevent overfitting in decision trees, you can use techniques like pruning, setting a maximum depth, or using ensemble methods.

What is pruning and how does it help?

Pruning involves removing sections of the tree that provide little power to classify instances, which helps reduce complexity and overfitting.

Are there specific algorithms for ensemble methods?

Yes, popular ensemble methods include Random Forests and Gradient Boosting, which combine multiple trees to improve accuracy and reduce overfitting.

How do I choose the right maximum depth for my tree?

Choosing the right maximum depth often involves experimentation and cross-validation to find a balance between bias and variance.