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Linear Model Selection: Linear Regression Basics

10 Questions

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Linear Model Selection: Linear Regression Basics

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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?

10,000

100,000

100

1,000 (correct)

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?

211 (correct)

210

220

What is a key advantage of Forward Stepwise Selection over Best Subset Selection?

Efficiency even with a large number of features Signup and view all the answers

What is a drawback of the Hybrid Approach in subset selection methods?

Final model may not always be the best possible Signup and view all the answers

What is the main objective of subset selection in linear model selection?

To reduce the number of predictors by eliminating irrelevant features Signup and view all the answers

In the context of linear model selection, what is the primary purpose of shrinkage techniques?

To decrease the magnitude of coefficient estimates towards zero Signup and view all the answers

Which approach in linear model selection involves projecting predictors into a lower-dimensional subspace?

Dimension Reduction Signup and view all the answers

What is the key difference between best subset selection and stepwise selection in linear model selection?

Best subset selection considers all possible subsets, while stepwise selection adds or removes one variable at a time. Signup and view all the answers

In linear model selection, what does the term 'regularization' refer to in the context of shrinkage techniques?

Shrinking coefficient estimates towards zero to prevent overfitting Signup and view all the answers