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Questions and Answers
What is a key advantage of bootstrapping?
What is a key advantage of bootstrapping?
- It eliminates the need for pruning in decision trees
- It guarantees accurate predictions for each data point
- It reduces variance compared with an ordinary tree (correct)
- It ensures sequential growth of trees for better model fit
How does boosting differ from bagging?
How does boosting differ from bagging?
- Boosting reduces variance compared with an ordinary tree, while bagging does not
- Bagging guarantees slow learning, while boosting allows for faster learning
- Boosting uses sequential growth, while bagging grows trees independently (correct)
- Bagging applies several weak learners one after the other, while boosting grows trees in parallel
What is a characteristic of AdaBoost?
What is a characteristic of AdaBoost?
- It guarantees accurate predictions for each data point
- It reduces variance compared with an ordinary tree
- It applies several weak-learners one after the other (correct)
- It grows trees independently from each other in parallel
Why is bagging considered a general-purpose technique?
Why is bagging considered a general-purpose technique?
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What is a characteristic of XGBoost (Extreme Gradient Boosting)?
What is a characteristic of XGBoost (Extreme Gradient Boosting)?
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