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What is the purpose of pruning in Decision Trees?

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Question: What is the purpose of pruning in Decision Trees?

Options:

  1. To increase the depth of the tree
  2. To remove unnecessary branches
  3. To add more features
  4. To improve computational efficiency

Correct Answer: To remove unnecessary branches

Solution: 

Pruning is used to remove unnecessary branches from a Decision Tree to reduce complexity and prevent overfitting.

What is the purpose of pruning in Decision Trees?

Practice Questions

Q1
What is the purpose of pruning in Decision Trees?
  1. To increase the depth of the tree
  2. To remove unnecessary branches
  3. To add more features
  4. To improve computational efficiency

Questions & Step-by-Step Solutions

What is the purpose of pruning in Decision Trees?
  • Step 1: Understand that a Decision Tree is a model used for making decisions based on data.
  • Step 2: Know that sometimes, a Decision Tree can become too complex by creating too many branches.
  • Step 3: Realize that these extra branches can lead to overfitting, which means the model works well on training data but poorly on new data.
  • Step 4: Learn that pruning is the process of cutting off these unnecessary branches.
  • Step 5: Understand that by pruning, we simplify the tree, making it easier to understand and better at predicting new data.
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