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In the context of Decision Trees, what does 'pruning' refer to?
Practice Questions
Q1
In the context of Decision Trees, what does 'pruning' refer to?
Adding more branches to the tree
Removing branches to reduce complexity
Increasing the depth of the tree
Changing the splitting criteria
Questions & Step-by-Step Solutions
In the context of Decision Trees, what does 'pruning' refer to?
Steps
Concepts
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.
No concepts available.
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