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. 2017 Sep 12;7:11347. doi: 10.1038/s41598-017-11665-4

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© The Author(s) 2017

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Changes in misclassification rate of HARF and Bayes error (Eq. 16) for different number of trees are shown. For model with few trees, misclassification rate is higher compared to model with high number of trees. As expected, HARF misclassification rate is always higher compared to minimum Bayes error, but the difference is always minimal for models with different number of trees. Drug AZD − 6244 and cancer types Skin & CNS are used for the generation of these curves.