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This section includes 7 Mcqs, each offering curated multiple-choice questions to sharpen your Data Science knowledge and support exam preparation. Choose a topic below to get started.
1. |
For most classification models, each predictor will have a separate variable importance for each class. |
A. | True |
B. | False |
Answer» B. False | |
2. |
Which of the following argument is used to set importance values? |
A. | scale |
B. | set |
C. | value |
D. | all of the mentioned |
Answer» B. set | |
3. |
Which of the following model sums the importance over each boosting iteration? |
A. | Boosted trees |
B. | Bagged trees |
C. | Partial least squares |
D. | None of the mentioned |
Answer» B. Bagged trees | |
4. |
The advantage of using a model-based approach is that is more closely tied to the model performance. |
A. | True |
B. | False |
Answer» B. False | |
5. |
Which of the following function tracks the changes in model statistics? |
A. | varImp |
B. | varImpTrack |
C. | findTrack |
D. | none of the mentioned |
Answer» B. varImpTrack | |
6. |
Which of the following curve analysis is conducted on each predictor for classification? |
A. | NOC |
B. | ROC |
C. | COC |
D. | All of the mentioned |
Answer» C. COC | |
7. |
varImp is a wrapper around the evimp function in the _______ package. |
A. | numpy |
B. | earth |
C. | plot |
D. | none of the mentioned |
Answer» C. plot | |