hasantuberlin / hyfd

HyFD for Python

Implementation of the HyFD functional dependency miner for python. This implementation was created for comparison purposes. Description of the original algorithms can be found in:

Thorsten Papenbrock and Felix Naumann. 2016. A Hybrid Approach to Functional Dependency Discovery. In Proceedings of the 2016 International Conference on Management of Data (SIGMOD '16). ACM, New York, NY, USA, 821-833. DOI: https://doi.org/10.1145/2882903.2915203

Usage

$ python hyfd.py data/silly_example.csv

HyFD for Python (by VC)

positional arguments:
db_path path to the database .

optional arguments:

-h, --help show this help message and exit
-s separator, --separator separator Value separator
-efft efficiency threshold (between 0 and 1)
-lf learning factor (between 0 and 1)
-ift invalid fds threshold (between 0 and 1)