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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 build a model that uses xyz regression.
You need to estimate a model that predicts a binary variable.
Which function should you use?
A. rxLogit
B. summary
C. rxLinMod
D. rxTweedie
E. rxPredict
F. stepAic
G. rxTransform
H. rxDataStep
Answer: A
References: https://docs.microsoft.com/en-us/r-server/r/how-to-revoscaler-logistic-regression

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(transforms = 'removeMissing')
C. rxDataStep(transformFunc = 'removeMissing')
D. rxDataStep(removeMissingsOnRead = FALSE, removeMissing = TRUE)
Answer: D

You need to build a model that looks at the probability of an outcome. You must regulate between L1 and L2.
Which classification method should you use?
A. Two-Class Neutral Network
B. Two-Class Support Vector Machine
C. Two-Class Decision Forest
D. Two-Class Logistic Regression
Answer: D
References: https://msdn.microsoft.com/en-us/library/azure/dn905994.aspx

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. categoricalHash()
B. featurizeText()
C. concat()
D. selectFeatures()
E. categorical()
Answer: B
References: https://docs.microsoft.com/en-us/machine-learning-server/python- reference/microsoftml/featurize-text

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PDF Questions & Answers

Exam Code: 070-773
Exam Name: Analyzing Big Data with Microsoft R
Updated: January 20, 2018
Total Q&As:40
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Exam Code: 070-773
Exam Name: Analyzing Big Data with Microsoft R
Updated: January 20, 2018
Total Q&As:40
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Exam Code: 070-773
Exam Name: Analyzing Big Data with Microsoft R
Updated: January 20, 2018
Total Q&As:40
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