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What does pruning refer to in the context of Decision Trees?

Practice Questions

Q1
What does pruning refer to in the context of Decision Trees?
  1. Adding more nodes to the tree
  2. Removing nodes to reduce complexity
  3. Increasing the depth of the tree
  4. Changing the splitting criterion

Questions & Step-by-Step Solutions

What does pruning refer to in the context of Decision Trees?
  • Step 1: Understand that a Decision Tree is a model used for making decisions based on data.
  • Step 2: Know that sometimes Decision Trees can become too complex by having too many branches or nodes.
  • Step 3: Realize that this complexity can lead to overfitting, which means the model performs well on training data but poorly on new data.
  • Step 4: Pruning is the process of simplifying the Decision Tree by removing some of these branches or nodes.
  • Step 5: The goal of pruning is to make the Decision Tree simpler, more general, and better at predicting new data.
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