ISYE 6414 Final Exam Questions With Correct Verified Answers A+ Graded
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Course
ISYE 6414
Institution
ISYE 6414
1. If there are variables that need to be used to control the bias selection in the model, they should be forced to be in the model and not be part of the variable selection process. - ANS True
2. Penalization in linear regression models means penalizing for complex models, that is, models wit...
, 1. If there are variables that need to be used to control the bias
selection in the model, they should be forced to be in the model and
not be part of the variable selection process. - ANS True
2. Penalization in linear regression models means penalizing for
complex models, that is, models with a large number of predictors. -
ANS True
K
3. Elastic net regression uses both penalties of the ridge and lasso
regression and hence combines the benefits of both. - ANS True
C
4. Variable selection can be applied to regression problems when the
LO
number of pre- dicting variables is larger than the number of
observations. - ANS True
5. The lasso regression performs well under multicollineariy. - ANS
YC
False
6. The selected variables using best subset regression are the best
ones in explaining and predicting the response variables. - ANS
D
False
U
8. The lasso regression requires a numerical algorithm to minimize the
penalized sum of least squares. - ANS True
ST
9. An unbiased estimator of the prediction risk is the training risk. -
ANS False
10. Backward and forward stepwise regression will generally provide
different sets of selected variables when p, the number of predicting
variables, is large. - ANS True
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