PipelineDP is a Python framework for applying differentially private aggregations to large datasets using batch processing systems such as Apache Spark, Apache Beam, and more.
Before this PR, the query noise std deviation was computed with assumption that the metric is COUNT/PRICACY_ID_COUNT. This PR changes that, along the way it switches to the usage of the new API of adding noise (AdditiveMechanism).
Before this PR, the query noise std deviation was computed with assumption that the metric is COUNT/PRICACY_ID_COUNT. This PR changes that, along the way it switches to the usage of the new API of adding noise (AdditiveMechanism).