QuestionApril 30, 2025

Which of the following adds random noise during model training to reduce the impact of any single individual on the model's outcomes and to give a guarantee that an individual in the training data set could not be identified? Model anonymization Differential privacy Referential reduction Data minimization

Which of the following adds random noise during model training to reduce the impact of any single individual on the model's outcomes and to give a guarantee that an individual in the training data set could not be identified? Model anonymization Differential privacy Referential reduction Data minimization
Which of the following adds random noise during model training to reduce the impact of any single individual on the model's outcomes and to give a guarantee that an individual in the training data set could not be identified? Model anonymization Differential privacy Referential reduction Data minimization

Solution
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Answer

Differential privacy Explanation 1. Identify the concept Differential privacy is a technique that adds random noise during model training to ensure that individual data points cannot be identified, providing privacy guarantees.

Explanation

1. Identify the concept<br /> Differential privacy is a technique that adds random noise during model training to ensure that individual data points cannot be identified, providing privacy guarantees.
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