In the context of Decision Trees, what does 'pruning' refer to?

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Question: In the context of Decision Trees, what does \'pruning\' refer to?

Options:

Correct Answer: Removing branches to reduce complexity

Solution:

Pruning is the process of removing branches from a Decision Tree to prevent overfitting and improve generalization.

In the context of Decision Trees, what does 'pruning' refer to?

In the context of Decision Trees, what does 'pruning' refer to?

Step 1: Understand what a Decision Tree is. It is a model used for making decisions based on data.
Step 2: Learn that a Decision Tree can become too complex by creating many branches, which can lead to overfitting.
Step 3: Overfitting means the model works well on training data but poorly on new, unseen data.
Step 4: Pruning is the method used to simplify the Decision Tree by removing some branches.
Step 5: By removing these branches, the model becomes less complex and can generalize better to new data.

Pruning in Decision Trees – Pruning is the process of removing branches from a Decision Tree to prevent overfitting and improve generalization.