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. 2022 Sep 27;8:112. doi: 10.1038/s41523-022-00480-4

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© The Author(s) 2022

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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Fig. 5 — a On the left, ROC analysis of the random forest model for each target variable class. Curves represent merged prediction from folds. On the right, AUC and F1 score of the corresponding models. b Confusion matrix of the random forest model on the test set. c Ranking of the features for classification based on information gain. Each color represents a channel-classified event group detailed marked in the figure.