TY - RPRT ID - mr2019barxiv T1 - Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy A1 - Rapp, Michael A1 - Loza Mencía, Eneldo A1 - Fürnkranz, Johannes Y1 - 2019 M1 - ArXiv e-prints IS - 1911.04393 T2 - Knowledge Engineering Group, Technische Universität Darmstadt UR - https://arxiv.org/abs/1911.04393 N2 - 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. M1 - archiveprefix={arXiv} M1 - eprint={1911.04393} M1 - primaryclass={cs.LG} ER -