Data Science Questions and Answers – Cross Validation

This set of Data Science Multiple Choice Questions & Answers (MCQs) focuses on “Cross Validation”.

1. Which of the following is correct use of cross validation?
a) Selecting variables to include in a model
b) Comparing predictors
c) Selecting parameters in prediction function
d) All of the mentioned
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2. Point out the wrong combination.
a) True negative=correctly rejected
b) False negative=correctly rejected
c) False positive=correctly identified
d) All of the mentioned
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3. Which of the following is a common error measure?
a) Sensitivity
b) Median absolute deviation
c) Specificity
d) All of the mentioned
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4. Which of the following is not a machine learning algorithm?
a) SVG
b) SVM
c) Random forest
d) None of the mentioned
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5. Point out the wrong statement.
a) ROC curve stands for receiver operating characteristic
b) Foretime series, data must be in chunks
c) Random sampling must be done with replacement
d) None of the mentioned
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6. Which of the following is a categorical outcome?
a) RMSE
b) RSquared
c) Accuracy
d) All of the mentioned
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7. For k cross-validation, larger k value implies more bias.
a) True
b) False
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8. Which of the following method is used for trainControl resampling?
a) repeatedcv
b) svm
c) bag32
d) none of the mentioned
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9. Which of the following can be used to create the most common graph types?
a) qplot
b) quickplot
c) plot
d) all of the mentioned
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10. For k cross-validation, smaller k value implies less variance.
a) True
b) False
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