You have a dataset that includes confidential data. You use the dataset to train a model. You must use a differential privacy parameter to keep the data of individuals safe and private. You need to…

Question

Options

• ADecrease the value of the epsilon parameter to reduce the amount of noise added to the data
• BIncrease the value of the epsilon parameter to decrease privacy and increase accuracy
• CDecrease the value of the epsilon parameter to increase privacy and reduce accuracy
• DSet the value of the epsilon parameter to 1 to ensure maximum privacy

• A
  4% (1)
• C
  92% (24)
• D
  4% (1)

Explanation

Differential privacy tries to protect against the possibility that a user can produce an indefinite number of reports to eventually reveal sensitive data. A value known as epsilon measures how noisy, or private, a report is. Epsilon has an inverse relationship to noise or privacy. The lower the epsilon, the more noisy (and private) the data is. https://docs.microsoft.com/en-us/azure/machine-learning/concept-differential-privacy

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