Machine Learning: The Future of Data Analysis MCQ part-5

Que.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
Que.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
Que.Which of the following is a common error measure?
a. Sensitivity
b. Median absolute deviation
c. Specificity
d. All of the mentioned
Que.Which of the following is not a machine learning algorithm?
a. SVG
b. SVM
c. Random forest
d. None of the mentioned
Que.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
Que.Which of the following is a categorical outcome?
a. RMSE
b. RSquared
c. Accuracy
d. All of the mentioned
Que.For k cross-validation, larger k value implies more bias.
a. True
b. False
c. May be True or False
d. Can’t say
Que.Which of the following method is used for trainControl resampling?
a. repeatedcv
b. svm
c. bag32
d. none of the mentioned
Que.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
Que.For k cross-validation, smaller k value implies less variance.
a. True
b. False
c. May be True or False
d. Can’t say
Que.Predicting with trees evaluate _____________ within each group of data.
a. equality
b. homogeneity
c. heterogeneity
d. all of the mentioned
Que.Point out the wrong statement.
a. Training and testing data must be processed in different way
b. Test transformation would mostly be imperfect
c. The first goal is statistical and second is data compression in PCA
d. All of the mentioned
Que.Which of the following method options is provided by train function for bagging?
a. bagEarth
b. treebag
c. bagFDA
d. all of the mentioned
Que.Which of the following is correct with respect to random forest?
a. Random forest are difficult to interpret but often very accurate
b. Random forest are easy to interpret but often very accurate
c. Random forest are difficult to interpret but very less accurate
d. None of the mentioned
Que.Point out the correct statement.
a. Prediction with regression is easy to implement
b. Prediction with regression is easy to interpret
c. Prediction with regression performs well when linear model is correct
d. All of the mentioned