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Code for our paper "Fair k-Center Clustering for Data Summarization"
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README.md Update README.md Apr 26, 2019
algorithm_matroid_center.py added matroid-center Feb 21, 2019
algorithms.py made some changes Feb 21, 2019
experiments_adult_data_set.py
experiments_artificial_data.py
experiments_matroid_center.py added matroid-center Feb 21, 2019

README.md

fair_k_center_clustering

Code for our paper "Fair k-Center Clustering for Data Summarization" (https://arxiv.org/abs/1901.08628).

To try it out and reproduce the boxplots (based on 10 runs) of the experiments of Figures 4 to 6 on artificial data, simply run

python experiments_artificial_data.py 

If you want to obtain the boxplots based on 50 runs, say, then run

python experiments_artificial_data.py 50

Similarly, in order to reproduce the boxplots of the experiments of Figures 5 and 6 on the Adult data set, run

python experiments_adult_data_set.py 50

If you want to compare our algorithm to the algorithm for the matroid center problem by Chen et al. (https://arxiv.org/abs/1301.0745), you need to have SageMath (http://www.sagemath.org/) installed on your system. Then simply run

sage -python experiments_matroid_center.py 50

The code has been tested with the following software versions:

  • Python 2.7.10
  • Numpy 1.16.2
  • Scipy 1.1.0
  • Scikit-learn 0.19.1
  • Pandas 0.23.0
  • SageMath 8.2
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