/DiffGen

Differentially private data release for data mining [SIGKDD 2011] - convert a relational data set into a differentially-private version while maintaining its capability for data mining

Primary LanguageC++OtherNOASSERTION

DiffGen

Differentially private data release for data mining [SIGKDD 2011]

License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License

Owners: Noman Mohammed, Rui Chen, and Benjamin C. M. Fung

Publication:

N. Mohammed, R. Chen, B. C. M. Fung, and P. S. Yu. Differentially private data release for data mining. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), pages 493-501, San Diego, CA: ACM Press, August 2011.

Disclaimer:

The software is provided as-is with no warranty or support. We do not take any responsibility for any damage, loss of income, or any problems you might experience from using our software. If you have questions, you are encouraged to consult the paper and the source code. If you find our software useful, please cite our paper above.

The Adult data set can also be obtained from: http://www.ics.uci.edu/~mlearn/MLRepository.html