imodels/references.bib

@article{ustun2016supersparse,
  title={Supersparse linear integer models for optimized medical scoring systems},
  author={Ustun, Berk and Rudin, Cynthia},
  journal={Machine Learning},
  volume={102},
  number={3},
  pages={349--391},
  year={2016},
  publisher={Springer}
}

@article{pedregosa2011scikit,
  title={Scikit-learn: Machine learning in Python},
  author={Pedregosa, Fabian and Varoquaux, Ga{\"e}l and Gramfort, Alexandre and Michel, Vincent and Thirion, Bertrand and Grisel, Olivier and Blondel, Mathieu and Prettenhofer, Peter and Weiss, Ron and Dubourg, Vincent and others},
  journal={the Journal of machine Learning research},
  volume={12},
  pages={2825--2830},
  year={2011},
  publisher={JMLR. org}
}

@article{letham2015interpretable,
  title={Interpretable classifiers using rules and bayesian analysis: Building a better stroke prediction model},
  author={Letham, Benjamin and Rudin, Cynthia and McCormick, Tyler H and Madigan, David and others},
  journal={Annals of Applied Statistics},
  volume={9},
  number={3},
  pages={1350--1371},
  year={2015},
  publisher={Institute of Mathematical Statistics}
}

@article{holte1993very,
  title={Very simple classification rules perform well on most commonly used datasets},
  author={Holte, Robert C},
  journal={Machine learning},
  volume={11},
  number={1},
  pages={63--90},
  year={1993},
  publisher={Springer}
}

@book{breiman1984classification,
  title={Classification and regression trees},
  author={Breiman, Leo and Friedman, Jerome and Stone, Charles J and Olshen, Richard A},
  year={1984},
  publisher={CRC press}
}

@book{molnar2020interpretable,
  title={Interpretable machine learning},
  author={Molnar, Christoph},
  year={2020},
  publisher={Lulu. com}
}

@article{rudin2018please,
  title={Please stop explaining black box models for high stakes decisions},
  author={Rudin, Cynthia},
  journal={arXiv preprint arXiv:1811.10154},
  volume={1},
  year={2018},
  publisher={Nov}
}

@article{murdoch2019definitions,
  title={Definitions, methods, and applications in interpretable machine learning},
  author={Murdoch, W James and Singh, Chandan and Kumbier, Karl and Abbasi-Asl, Reza and Yu, Bin},
  journal={Proceedings of the National Academy of Sciences},
  volume={116},
  number={44},
  pages={22071--22080},
  year={2019},
  publisher={National Acad Sciences}
}

@article{friedman2008predictive,
  title={Predictive learning via rule ensembles},
  author={Friedman, Jerome H and Popescu, Bogdan E and others},
  journal={Annals of Applied Statistics},
  volume={2},
  number={3},
  pages={916--954},
  year={2008},
  publisher={Institute of Mathematical Statistics}
}

@misc{skope,
  author = {{Skope Collaboration}},
  title = {Skope-rules},
  year = {2021},
  publisher = {GitHub},
  journal = {GitHub repository},
  url = {https://github.com/scikit-learn-contrib/skope-rules}
}