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API Reference


The Diffprivlib library implements differential privacy techniques for various data analysis tasks. It can be viewed as a differentialy private version of scikit-learn, implementing the DP-equivalents of many of the sklearn models. The library provides multiple functionalities, including mechanisms for adding noise to data, privacy-preserving machine learning algorithms, and statistical analysis tools.

Currently, AG supports all the methods and classes within the following directories:

AG uses the same interfaces with the same function names and signatures. However, op_diffprivlib has additional privacy implementations. op_diffprivlib enforces that functions which output data to only return PrivateDataFrame if PrivateDataFrame is an input and return pandas.DataFrame if pandas.DataFrame is an input.

You can access the official Official Diffprivlib docs page to learn more about all the function signatures and methods.