Data Science

caret

Question 1
Marks : +2 | -2
Pass Ratio : 100%
Point out the wrong statement.
Simple random sampling of time series is probably the best way to resample times series data.
Three parameters are used for time series splitting
Horizon parameter is the number of consecutive values in test set sample
All of the mentioned
Explanation:
Simple random sampling of time series is probably not the best way to resample times series data.
Question 2
Marks : +2 | -2
Pass Ratio : 100%
caret does not use the proxy package.
True
False
Explanation:
caret uses the proxy package.
Question 3
Marks : +2 | -2
Pass Ratio : 100%
Which of the following can be used to generate balanced cross–validation groupings from a set of data?
createFolds
createSample
createResample
none of the mentioned
Explanation:
createResample can be used to make simple bootstrap samples.
Question 4
Marks : +2 | -2
Pass Ratio : 100%
Point out the correct statement.
The difference between the class centroids and the overall centroid is used to measure the variable influence
The Bagged Trees output contains variable usage statistics
Boosted Trees uses different approach as a single tree
None of the mentioned
Explanation:
The larger the difference between the class centroid and the overall center of the data, the larger the separation between the classes.
Question 5
Marks : +2 | -2
Pass Ratio : 100%
Which of the following can be used to create sub–samples using a maximum dissimilarity approach?
minDissim
maxDissim
inmaxDissim
all of the mentioned
Explanation:
Splitting is based on the predictors.
Question 6
Marks : +2 | -2
Pass Ratio : 100%
Point out the correct statement.
findLinearColumns will also return a vector of column positions can be removed to eliminate the linear dependencies
findLinearCombos will return a list that enumerates dependencies
the function findLinearRows can be used to generate a complete set of row variables from one factor
none of the mentioned
Explanation:
For each linear combination, it will incrementally remove columns from the matrix and test to see if the dependencies have been resolved.
Question 7
Marks : +2 | -2
Pass Ratio : 100%
Which of the following function can be used to flag predictors for removal?
searchCorrelation
findCausation
findCorrelation
none of the mentioned
Explanation:
Some models thrive on correlated predictors.
Question 8
Marks : +2 | -2
Pass Ratio : 100%
Which of the following function can be used to create balanced splits of the data?
newDataPartition
createDataPartition
renameDataPartition
none of the mentioned
Explanation:
If the y argument to this function is a factor, the random sampling occurs within each class and should preserve the overall class distribution of the data.
Question 9
Marks : +2 | -2
Pass Ratio : 100%
Which of the following model sums the importance over each boosting iteration?
Boosted trees
Bagged trees
Partial least squares
None of the mentioned
Explanation:
gbm package can be used here.
Question 10
Marks : +2 | -2
Pass Ratio : 100%
Which of the following function tracks the changes in model statistics?
varImp
varImpTrack
findTrack
none of the mentioned
Explanation:
GCV change value can also be tracked.