Q.1.
varImp is a wrapper around the evimp function in the _______ package.
Q.2.
Point out the wrong statement.
Q.3.
Which of the following curve analysis is conducted on each predictor for classification?
Q.4.
Which of the following function tracks the changes in model statistics?
Q.5.
Point out the correct statement.
Q.6.
Which of the following model model include a backwards elimination feature selection routine?
Q.7.
The advantage of using a model-based approach is that is more closely tied to the model performance.
Q.8.
Which of the following model sums the importance over each boosting iteration?
Q.9.
Which of the following argument is used to set importance values?
Q.10.
For most classification models, each predictor will have a separate variable importance for each class.