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. 2022 Jan 11;6:1. doi: 10.1186/s41512-021-00115-5

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© The Author(s) 2022

Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 7 — Hyperparameter values for xerostomia: per predictor set, setting A being the small predictor set with high EPV (EPV = 23), and setting B the large predictor set with lower EPV (EPV = 8). The high collinearity settings in red, and the low collinearity setting in blue. The methods are distributed across three plots due to their different scales. Hyperparameter notation follows Table 2, except for λ_ENet , which is the total shrinkage factor for ElasticNet (λ_ℓ1 +λ_ℓ2 )