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This package brings redescription model mining to python.

Get some python packages

git clone https://github.com/Feelx234/pyRDMM.gitgit clone https://github.com/flemmerich/pysubgroup.git

Create virtual environment

python -m venv envsource ./env/bin/activatepip install -e pysubgroup/pip install -e pyRDMM/pip instal jupyter

To tun the experiments on synthetic data move into the scripts folder of pyRDMM.

cd ./pyRDMM/scripts/

You should now configure therun_experiments.py such that those experiments are executed. If you execute all the experiments be aware that running them will take about 20h.you can run those with the virtual environment activated by

python run_experiments.py

After all the experiments are finished the scriptexport_eval_results.ipynb can be used to create plots and to export the results in a more human readable fashion.

We performed two experiments on real world datasets. One on a housing dataset available at kaggle and a second experiment with survey data for the European Social Survey (ESS).

To run the house price experiments you will need to download the data manually from kaggle. The corresponding links are:

• https://www.kaggle.com/dansbecker/melbourne-housing-snapshot and
• https://www.kaggle.com/ruiqurm/lianjia.

To then run the experiments for the house price data consider the scriptreal_data_housing.ipynb inpyRDMM/scripts/. There all you need to do is adjust thefolder in the second cell to point to the locations where the downloaded files are located.