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Questions and Answers
What is the goal of a decision tree?
What is the goal of a decision tree?
- To segment the predictor space into simple regions (correct)
- To create complex boundaries for continuous variables
- To maximize entropy in the data set
- To minimize information gain from the split
What does pruning in decision trees aim to achieve?
What does pruning in decision trees aim to achieve?
- Reduce overfitting by limiting tree depth (correct)
- Maximize impurity in terminal nodes
- Increase overfitting by expanding tree depth
- Minimize information gain from root splits
What does bagging involve in ensemble learning?
What does bagging involve in ensemble learning?
- Aggregating the results of identical models
- Creating multiple decision trees trained on different bootstrap samples (correct)
- Creating a single decision tree trained on multiple bootstrap samples
- Training decision trees on the entire data set without sampling
How are continuous features handled before a split at the root node in a decision tree?
How are continuous features handled before a split at the root node in a decision tree?
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What is the purpose of creating ensembles in machine learning?
What is the purpose of creating ensembles in machine learning?
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