Q.1
varImp is a wrapper around the evimp function in the _______ package.
  • a) numpy
  • b) earth
  • c) plot
  • d) none of the mentioned
Q.2
Point out the wrong statement.
  • a) The trapezoidal rule is used to compute the area under the ROC curve
  • b) For regression, the relationship between each predictor and the outcome is evaluated
  • c) An argument, para, is used to pick the model fitting technique
  • d) All of the mentioned
Q.3
Which of the following curve analysis is conducted on each predictor for classification?
  • a) NOC
  • b) ROC
  • c) COC
  • d) All of the mentioned
Q.4
Which of the following function tracks the changes in model statistics?
  • a) varImp
  • b) varImpTrack
  • c) findTrack
  • d) none of the mentioned
Q.5
Point out the correct statement.
  • a) The difference between the class centroids and the overall centroid is used to measure the variable influence
  • b) The Bagged Trees output contains variable usage statistics
  • c) Boosted Trees uses different approach as a single tree
  • d) None of the mentioned
Q.6
Which of the following model model include a backwards elimination feature selection routine?
  • a) MCV
  • b) MARS
  • c) MCRS
  • d) All of the mentioned
Q.7
The advantage of using a model-based approach is that is more closely tied to the model performance.
  • a) True
  • b) False
Q.8
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
Q.9
Which of the following argument is used to set importance values?
  • a) scale
  • b) set
  • c) value
  • d) all of the mentioned
Q.10
For most classification models, each predictor will have a separate variable importance for each class.
  • a) True
  • b) False
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