Online Access Free 070-773 Practice Test

You have one-class support vector machines (SVMs).
You have a large dataset, but you do not have enough training time to fully test the model.
What is an alternative method to validate the model?

• A.Replace the SVMs with two-class SVMs.
• B.Use outlier detection.
• C.Use Principal Components Analysis (PCA)-Based Anomaly Detection.
• D.Perform feature selection.

Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
Start of repeated scenario
You are developing a Microsoft R Open solution that will leverage the computing power of the database server for some of your datasets.
You are performing feature engineering and data preparation for the datasets.
The following is a sample of the dataset.

End of repeated scenario.
You need to analyze the dataset without the missing values. The solution must not remove the missing values from the dataset.
Which R code segment should you use?

• A.rxDataStep(removeMissingsOnRead = FALSE, removeMissing = TRUE)
• B.rxDataStep(transformFunc = 'removeMissing')
• C.rxDataStep(varsToDrop = NULL)
• D.rxDataStep(transforms = 'removeMissing')

You are running a parallel function that uses the following R code segment. (Line numbers are included for reference only.)
0 1 cp <- 0.01 xval <- 0 maxdepth <- 5
0 2
0 3 (form, data = "segmentationDataBig", maxDepth = maxdepth, cp = cp, xval = xval, blocksPerRead = 250 You need to complete the R code. The solution must support chunking.
Which function should insert at line 02?

• A.rxExec
• B.rxBTrees
• C.rxDForest
• D.rxDTree

Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question.
You have a data source that is larger than memory.
You need to visualize the distribution of the values for a variable in the data source.
What should you use?

• A.the rxCrossTabs function
• B.the ggplot2 package
• C.the rxCube function
• D.the rxHistogram function
• E.the rxSummary function
• F.the summary function
• G.the Describe package
• H.the rxQuantile function

You have a slow Map Reduce job.
You need to optimize the job to control the number of mapper and runner tasks.
Which function should you use?

• A.RxHadoopMR
• B.rxExec
• C.RxComputeContext
• D.RxLocalParallel