What is pre-pruning in decision trees?
An example of an AI chatbot conversation about pre-pruning in decision trees.
What is pre-pruning in decision trees?
Pre-pruning is a technique used in decision tree algorithms to stop the tree from growing too complex by halting the splitting of nodes.
Why is pre-pruning important?
Pre-pruning helps to prevent overfitting, which can occur when a model is too complex and captures noise in the training data.
How does pre-pruning differ from post-pruning?
Pre-pruning stops the tree from growing during the training process, while post-pruning involves trimming the tree after it has been fully grown.
Can you give an example of pre-pruning?
Sure! An example of pre-pruning is setting a maximum depth for the tree or requiring a minimum number of samples in a node before splitting.
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