What is the main purpose of pruning a Decision Tree?

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Question: What is the main purpose of pruning a Decision Tree?

Options:

Correct Answer: To reduce the size of the tree and prevent overfitting

Solution:

Pruning reduces the size of the tree, which helps to prevent overfitting and improves generalization to unseen data.

What is the main purpose of pruning a Decision Tree?

What is the main purpose of pruning a Decision Tree?

Step 1: Understand what a Decision Tree is. It is a model used for making decisions based on data.
Step 2: Know that a Decision Tree can become very large and complex, which can lead to overfitting.
Step 3: Overfitting means the tree learns the training data too well, including noise, and performs poorly on new data.
Step 4: Pruning is the process of cutting back the tree to make it smaller and simpler.
Step 5: By pruning, we remove unnecessary branches that do not help in making accurate predictions.
Step 6: A smaller tree is easier to understand and usually performs better on unseen data.
Step 7: The main purpose of pruning is to improve the model's ability to generalize to new data.

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