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Questions and Answers
In Best Subset Selection, how many potential models are there when the number of features (p) is 10?
In Best Subset Selection, how many potential models are there when the number of features (p) is 10?
- 10,000
- 100,000
- 100
- 1,000 (correct)
What is a disadvantage of Best Subset Selection as compared to Forward Stepwise Selection?
What is a disadvantage of Best Subset Selection as compared to Forward Stepwise Selection?
- Guarantees finding the best model
- Inefficient in handling large feature sets (correct)
- Less computationally intense
- Limited to smaller feature sets
In Stepwise Selection, what is the total number of models considered when p = 20 and using the Backward selection method?
In Stepwise Selection, what is the total number of models considered when p = 20 and using the Backward selection method?
- 211 (correct)
- 210
- 220
- 20
What is a key advantage of Forward Stepwise Selection over Best Subset Selection?
What is a key advantage of Forward Stepwise Selection over Best Subset Selection?
What is a drawback of the Hybrid Approach in subset selection methods?
What is a drawback of the Hybrid Approach in subset selection methods?
What is the main objective of subset selection in linear model selection?
What is the main objective of subset selection in linear model selection?
In the context of linear model selection, what is the primary purpose of shrinkage techniques?
In the context of linear model selection, what is the primary purpose of shrinkage techniques?
Which approach in linear model selection involves projecting predictors into a lower-dimensional subspace?
Which approach in linear model selection involves projecting predictors into a lower-dimensional subspace?
What is the key difference between best subset selection and stepwise selection in linear model selection?
What is the key difference between best subset selection and stepwise selection in linear model selection?
In linear model selection, what does the term 'regularization' refer to in the context of shrinkage techniques?
In linear model selection, what does the term 'regularization' refer to in the context of shrinkage techniques?
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