ISYE 6414 Final Correctly Answered 2025 Update
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ISYE 6414
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ISYE 6414
ISYE 6414 Final Correctly Answered 2025 Update 1. If there are variables that need to be used to control the bias selection in the model, they should forced to be in the model and not being part of the variable selection process. - Answer -True 2. Pe...
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| Uploaded on: | June 3, 2025 |
| Last updated: | June 3, 2025 |
| Number of pages: | 5 |
| Written in: | 2025/2026 |
| Type: | Exam (elaborations) |
| Contains: | Questions & Answers |
| Tags: | ISYE 6414 Final Correctly Answered 2025 Update 1. If there are variables that need to be used to control the bias selection in the model, they should forced to be in the model and not being part of the variable selection process. - Answer -True 2. Penalization in linear regression models means penalizing for complex models, that is, models with a large number of predictors. - Answer -True 3. Elastic net regression uses both penalties of the ridge and lasso regression and hence co |
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ISYE 6414 Final Correctly Answered 2025 Update 1. If there are variables that need to be used to control the bias selection in the model, they should forced to be in the model and not being part of the variable selection process. - Answer -True 2. Penalization in linear regression models means penalizing for complex models, that is, models with a large number of predictors. Answer -True 3. Elastic net regression uses both penalties of the ridge and lasso regression and hence combines the benefits of both. - Answer -True 4. Variable selection can be applied to regression problems when the number of pre- dicting variables is larger than the number of observations. - Answer -True 5. The lasso regression performs well under multicollineariy. - Answer False 6. The selected variables using best subset regression are the best ones in explaining and predicting the response variables. - Answer -False 8. The lasso regression requires a numerical algorithm to minimize the penalized sum of least squares. - Answer -True 9. An unbiased estimator of the prediction risk is the training risk. Answer -False
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