%Aigaion2 BibTeX export from Knowledge Engineering Publications
%Tuesday 29 September 2020 10:00:51 PM

@TECHREPORT{mr2019barxiv,
       author = {Rapp, Michael and Loza Menc{\'{\i}}a, Eneldo and F{\"{u}}rnkranz, Johannes},
        month = sep,
        title = {Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy},
         type = {ArXiv e-prints},
       number = {1911.04393},
         year = {2019},
  institution = {Knowledge Engineering Group, Technische Universit{\"{a}}t Darmstadt},
          url = {https://arxiv.org/abs/1911.04393},
     abstract = {We analyze the trade-off between model complexity and accuracy for random forests by breaking the trees up into individual classification rules and selecting a subset of them. We show experimentally that already a few rules are sufficient to achieve an acceptable accuracy close to that of the original model. Moreover, our results indicate that in many cases, this can lead to simpler models that clearly outperform the original ones.},
archiveprefix={arXiv}, eprint={1911.04393}, primaryclass={cs.LG},
}