Microsoft Analyzing Big Data with Microsoft R - 070-773 FREE EXAM DUMPS QUESTIONS & ANSWERS
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?
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?
Correct Answer: A
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DRAG DROP
You are using rxPredict for a logistic regression model.
You need to obtain prediction standard errors and confidence intervals.
Which R code segment should you use? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
You are using rxPredict for a logistic regression model.
You need to obtain prediction standard errors and confidence intervals.
Which R code segment should you use? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
References: https://docs.microsoft.com/en-us/machine-learning-server/r/how-to-revoscaler-logistic-regression
HOTSPOT
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 sort the data from the dataset sample and to remove duplicates by using wkswork1.
Which R code segment should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
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 sort the data from the dataset sample and to remove duplicates by using wkswork1.
Which R code segment should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
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?
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?
Correct Answer: A
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