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QUESTION 6
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 have the following R code.

Which function determines the variable?

A. transformVars
B. rxXdfDataFrame
C. createRandomSample
D. transformFunc

Answer: A

QUESTION 7
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 need to evaluate the significance of coefficients that are produced by using a model that was estimated already.
Which function should you use?

A. rxPredict
B. rxLogit
C. summary
D. rxLinMod
E. rxTweedie
F. stepAic
G. rxTransform
H. rxDataStep

Answer: D
Explanation:
https://docs.microsoft.com/en-us/machine-learning-server/r/how-to-revoscaler-linear-model

QUESTION 8
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You use dplyrXdf, and you discover that after you exit the session, the output files that were created were deleted.
You need to prevent the files from being deleted.
Solution: You use rxSetComputeContext with the local parameter before performing operations that save results.
Does this meet the goal?

A. Yes
B. No

Answer: B

QUESTION 9
You need to use the ScaleR distributed processing in an Apache Hadoop environment.
Which data source should you use?

A. Microsoft SQL Server database
B. XDF data files
C. ODBC data
D. Teradata database

Answer: B
Explanation:
https://docs.microsoft.com/en-us/machine-learning-server/r/how-to-revoscaler-hadoop

QUESTION 10
You perform an analysis that produces the decision tree shown in the exhibit. (Click the Exhibit button.)

How many leaf nodes are there on the tree?

A. 2
B. 3
C. 5
D. 7

Answer: C
Section: (none)
Explanation/Reference:
Explanation:
https://docs.microsoft.com/en-us/machine-learning-server/r/how-to-revoscaler-decision-tree

QUESTION 11
You plan to read data from an Oracle database table and to store the data in the file system for later processing by dplyrXdf. The size of the data is larger than the memory on the server to be used for modelling.
You need to ensure that the data can be processed by dplyrXdf in the least amount of time possible.
How should you transfer the data from the Oracle database?

A. Define a data source to the Oracle database server by using RxOdbcData. Use rxImport to save the data to a comma-separated values (CSV) file.
B. Use the RODBC library, connect to the Oracle database server by using odbcConnect, and then use rxDataStep to export the data to a comma-separated values (CSV) file.
C. Define a data source to the Oracle database server by using RxOdbcData, and then use rxImport to save the data to an XDF file.
D. Use the RODBC library, connect to the Oracle database server by using odbcConnect, and then use rxSplit to save the data to multiple comma-separated values (CSV) file.

Answer: C

QUESTION 12
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 need to estimate a model where the outcome variable is continuous, is in the range of [0, inf], and has a substantial mass at an exact value of 0.
Which function should you use?

A. rxPredict
B. rxLogit
C. summary
D. rxLinMod
E. rxTweedie
F. stepAic
G. rxTransform
H. rxDataStep

Answer: F

QUESTION 13
You plan to analyze data on a local computer. To improve performance, you plan to alternate the operation between a Microsoft SQL Server and the local computer.
You need to run complex code on the SQL Server, and then revert to the local compute context.
Which R code segment should you use?

A. sqlCompute <-RxInSqlServer(connectionString = “Driver=SQL Server;Server = myServer; Database = TestDB; Uid = myID; Pwd = myPwd;”)sqlPackagePaths <-RxFindPackage(package = “RevoScaleR”, computeContext = sqlServerCompute)
B. sqlCompute <-RxInSqlServer(connectionstring = sqlConnString, shareDir = sqlShareDir,wait = sqlWait, consoleOutput =
sqlConsoleOutput)rxSetComputeContext(“local”)x <-1:10rxExec(print, x, elemType = “cores”, timesToRun = 10)rxSetComputeContext(“RxLocalParallel”)
C. sqlCompute <-RxInSqlServer(connectionstring = sqlConnString, shareDir = sqlShareDir,wait = sqlWait, consoleOutput =
sqlConsoleOutput)rxSetComputeContext(“sqlCompute”)x <-1:10rxExec(print, x, elemType = “cores”, timesToRun = 10)rxSetComputeContext(“local”)
D. sqlCompute <-RxInSqlServer(connectionstring = sqlConnString, shareDir = sqlShareDir,wait = sqlWait, consoleOutput =
sqlConsoleOutput)rxSetComputeContext(“local”)x <-1:10rxExec(print, x, elemType = “cores”, timesToRun = 10)rxSetComputeContext(“sqlCompute”)

Answer: D
Explanation:
https://docs.microsoft.com/en-us/sql/advanced-analytics/tutorials/deepdive-define-and-use-compute-contexts


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