Online Access Free 070-773 Practice Test

You have a dataset that has a character variable.
You need to create a bag of counts of n-grams.
Which function should you use?

• A.categorical()
• B.categoricalHash()
• C.concat()
• D.selectFeatures()
• E.featurizeText()

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

You have a Microsoft SQL Server instance that has R Services (In-Database) installed.
The server has a comma-separated values (CSV) file stored in the local file system.
For analytic purposes, you need to read the CSV file into a database table in the SQL Server instance.
You connect to the SQL Server instance by using SQL Server Management Studio.
What should you use from sp_execute_external_script?

• A.rxDataStep and specify the CSV file path as the inFile argument
• B.RxSqlServerData and specify the CSV file path in the connection string
• C.rxImportToXdf and specify specify the CSV file as the input
• D.read.csv and specify the CSV file path as the parameter

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 dplyrXdf with the outFile parameter and specify a path other than the working directory for dplyrXdf.
Does this meet the goal?

• A.Yes
• B.No

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.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.
• B.Define a data source to the Oracle database server by using RxOdbcData, and then use rxImport to save the data to an XDF file.
• C.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.
• D.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.