A suite of algorithms for finding interesting item sets in large databases by considering the item sets that compress the data best. Python implementations of the algorithms described in "Item Sets That Compress".
python main.py version filepath
To create a new environment:
python3 -m venv env
source env/bin/activate
To install packages in an active environment:
pip install <package name>
To save an environment:
pip freeze > requirements.txt
To restore an environment:
pip install -r ./requirements.txt
All datasets were taken from http://fimi.uantwerpen.be/data/. They can be found under the data
folder of this repository (with the exception of kosarak
, which is too large to add to the repository)
chess
connect
kosarak