DiffPriv is a differential privacy package for python
Patch Update
--help
command.Patch update
None.
--docs
command to view the documentation for DiffPriv--changelog
command to view the changelogThe first beta release of the first version of diffpriv. Includes:
v0.1.1 now includes the exponential mechanism. you can view how to use it in the README.md
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@quantum9Innovation @Quantalabs
Added the new Laplace Mechanism. A new method which allows for much more capability. This allows you to import .csv files and deferentially privatize the data and keep the original data too. It will create a new file for the deferentially privatized data. It also allows for any float value instead of just 0 or 1 like it is with random response. But here are all the advantages of the Laplace Mechanism function in DiffPriv.
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More Flexibility in your data and values |
Allows for .csv files to be used |
Allows for both datasets to be kept (the original and privatized data) |
Flexibility on how privatized your data can be and how much it can be altered by using the epsilon parameter |
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python3 -m pip install DiffPriv==0.0.2
This version only includes one function 😞. The function is random. It runs the random response mechanism.
random(response_list)
v0.0.2 might include: