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Exam DP-100 topic 3 question 122 discussion

Actual exam question from Microsoft's DP-100
Question #: 122
Topic #: 3
[All DP-100 Questions]

You have a dataset that is stored in an Azure Machine Learning workspace.

You must perform a data analysis for differential privacy by using the SmartNoise SDK.

You need to measure the distribution of reports for repeated queries to ensure that they are balanced.

Which type of test should you perform?

  • A. Bias
  • B. Privacy
  • C. Accuracy
  • D. Utility
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Suggested Answer: A 🗳️

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evangelist
4 days, 9 hours ago
Selected Answer: A
perform a Bias test. This test will help you verify that the differentially private mechanism is not introducing systematic errors in any particular direction, thereby maintaining the integrity and fairness of the analysis.
upvoted 4 times
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deyoz
3 months, 4 weeks ago
Selected Answer: A
No doubt! check this https://www.virtualidentity.be/what-is-differential-privacy-in-machine-learning-preview/ https://www.virtualidentity.be/what-is-differential-privacy-in-machine-learning-preview/
upvoted 3 times
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Panda_man
4 months, 2 weeks ago
A for sure
upvoted 1 times
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GHill1982
5 months ago
Selected Answer: B
The privacy loss tester will run the query on the dataset with the specified epsilon value for the specified number of times, and generate a report that shows the distribution of the query results, the privacy loss distribution, and the accuracy metrics.
upvoted 1 times
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vv_bb
6 months, 3 weeks ago
The answer is A - Privacy Test - Determines whether a report adheres to the conditions of differential privacy. - Accuracy Test - Measures whether the reliability of reports falls within the upper and lower bounds given a 95% confidence level. - Utility Test - Determines whether the confidence bounds of a report are close enough to the data while still maximizing privacy. - Bias Test - Measures the distribution of reports for repeated queries to ensure they aren’t unbalanced from here: https://www.virtualidentity.be/what-is-differential-privacy-in-machine-learning-preview/
upvoted 4 times
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bobML
9 months, 1 week ago
D To measure the distribution of reports for repeated queries and ensure that they are balanced when performing differential privacy analysis using the SmartNoise SDK, you should perform a Utility test. Utility testing assesses how well the privacy mechanism (in this case, the differential privacy technique) preserves the usefulness or utility of the data. It checks whether the results of repeated queries maintain the desired statistical properties and distribution while adding noise to protect individual privacy. Balancing utility and privacy is a key consideration in differential privacy analysis.
upvoted 1 times
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BR_CS
9 months, 4 weeks ago
Selected Answer: A
Bias, as explained in the source from avotofu
upvoted 1 times
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phdykd
10 months, 3 weeks ago
A bias
upvoted 2 times
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vish9
1 year ago
Selected Answer: A
Agree with comment from avotofu
upvoted 2 times
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avotofu
1 year, 2 months ago
A. Bias "Bias: DP algorithms on repeated runs should have a mean signed deviation close to zero and not have a statistically significant deviation greater or lower than zero." https://github.com/opendp/smartnoise-sdk/tree/main/eval/sneval
upvoted 4 times
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esimsek
1 year, 2 months ago
Selected Answer: D
D=Utility
upvoted 1 times
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Tommo565
1 year, 2 months ago
Selected Answer: D
D is correct
upvoted 2 times
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Jin_22
1 year, 2 months ago
Selected Answer: D
To measure the distribution of reports for repeated queries to ensure that they are balanced when performing data analysis for differential privacy using the SmartNoise SDK, you should perform a utility test. A utility test measures the quality of the output of a differentially private query and checks whether the output is still useful for the intended purpose. The utility of the output is typically assessed by comparing it to the non-private output and measuring the difference between the two. The goal is to ensure that the difference is not too large, so that the output of the differentially private query is still useful. In this case, measuring the distribution of reports for repeated queries is a way to check the utility of the differentially private query, as it will help you ensure that the output is balanced and not biased towards a particular result. Therefore, the correct answer is D. Utility.
upvoted 4 times
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C (25%)
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