[BibTeX] [RIS]
Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy
Type of publication: Techreport
Citation: mr2019barxiv
Type: ArXiv e-prints
Number: 1911.04393
Year: 2019
Month: September
Institution: Knowledge Engineering Group, Technische Universität 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.
Userfields: archiveprefix={arXiv}, eprint={1911.04393}, primaryclass={cs.LG},
Authors Rapp, Michael
Loza Mencía, Eneldo
Fürnkranz, Johannes