A Python library for data synthesis and evaluation
The recent enforcement of data privacy protection regulations, such as GDPR, has made data sharing more difficult. This tool intends to facilitate data sharing from a customer by synthesizing a dataset based on the original dataset for later machine learning.
There are two parts to this tool:
- Data synthesizer Synthesize a dataset based on the original dataset. It accepts CSV data as input, and output a synthesized dataset based on Differential Privacy. The algorithm in the data synthesizer reference to the paper ( http://dimacs.rutgers.edu/~graham/pubs/papers/privbayes-tods.pdf).
- Data utility evaluation Evaluate the data utility for the synthesized dataset. The original dataset and the synthesized dataset as the input, one utility evaluation report will be generated with several indicators.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size ds4ml-0.2.2-py3-none-any.whl (35.8 kB)||File type Wheel||Python version py3||Upload date||Hashes View|
|Filename, size ds4ml-0.2.2.tar.gz (27.8 kB)||File type Source||Python version None||Upload date||Hashes View|