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Questions and Answers
What is the purpose of pruning in decision tree models?
What is the purpose of pruning in decision tree models?
- To decrease overfitting by removing unnecessary splits (correct)
- To add more splits for better accuracy
- To increase model complexity
- To speed up the training process
In decision trees, what does the Gini index measure?
In decision trees, what does the Gini index measure?
- The information gain at each split
- The level of entropy in the dataset
- The impurity of a node's classes (correct)
- The depth of the decision tree
What is the main goal of selecting the subtree with the best validation assessment in decision tree pruning?
What is the main goal of selecting the subtree with the best validation assessment in decision tree pruning?
- To maximize training accuracy
- To minimize validation accuracy
- To prevent underfitting
- To improve generalization performance (correct)
How does pruning affect the complexity of decision tree models?
How does pruning affect the complexity of decision tree models?
What criteria are commonly used to select the best subtree during decision tree pruning?
What criteria are commonly used to select the best subtree during decision tree pruning?
What is the purpose of repeating the split search process using different x values in decision tree construction?
What is the purpose of repeating the split search process using different x values in decision tree construction?
In decision tree construction, what does pruning one split from the maximal tree aim to achieve?
In decision tree construction, what does pruning one split from the maximal tree aim to achieve?
Which factor is used to measure impurity in decision tree nodes during the split search process?
Which factor is used to measure impurity in decision tree nodes during the split search process?
What is the primary purpose of creating a sequence of models with increasing complexity in predictive modeling?
What is the primary purpose of creating a sequence of models with increasing complexity in predictive modeling?
How does tree pruning affect decision tree models?
How does tree pruning affect decision tree models?
What is the significance of selecting the subtree with the highest validation assessment during pruning?
What is the significance of selecting the subtree with the highest validation assessment during pruning?
In the context of model complexity and tree pruning, what is the main purpose of comparing validation assessment between tree complexities?
In the context of model complexity and tree pruning, what is the main purpose of comparing validation assessment between tree complexities?
Why is it important to prune decision trees during model development?
Why is it important to prune decision trees during model development?
What is the significance of selecting the subtree with the best assessment rating during model development?
What is the significance of selecting the subtree with the best assessment rating during model development?
How does pruning impact model complexity in decision trees?
How does pruning impact model complexity in decision trees?
What role does entropy play in the context of decision tree modeling?
What role does entropy play in the context of decision tree modeling?
When pruning a decision tree, what is a potential consequence of excessively aggressive pruning?
When pruning a decision tree, what is a potential consequence of excessively aggressive pruning?
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