Classification

Decision Tree

Machine Learning

January 8, 2021

What is Pruning?

Decision trees are notoriously famous for overfitting. Pruning is a regularization method which penalizes the length of tree, i.e. increases the value of cost function.

Pruning is of two types:

  1. Post Pruning(Backward Pruning): Full tree is generated and then the non-significant branches are pruned/removed.
  2. Pre Pruning(Forward Pruning): This approach stops the non-significant branches from generating.

by : Monis Khan

Quick Summary:

Decision trees are notoriously famous for overfitting. Pruning is a regularization method which penalizes the length of tree, i.e. increases the value of cost function. Pruning is of two types: Post Pruning(Backward Pruning): Full tree is generated and then the non-significant branches are pruned/removed. Pre Pruning(Forward Pruning): This approach stops the non-significant branches from generating.