Multi-Response (Multivariate) Interpretable Machine Learning R package mrIML version 2.2.0 Builds and interprets multi-response machine learning models using 'tidymodels' syntax. Users can supply a tidy model, and 'mrIML' automates the process of fitting multiple response models to multivariate data and applying interpretable machine learning techniques across them. For more details see Fountain-Jones (2021) <doi:10.1111/1755-0998.13495> and Fountain-Jones et al. (2024) <doi:10.22541/au.172676147.77148600/v1>. Software Depends: R (>= 3.5.0) Imports: dplyr, magrittr, rlang, ggplot2, patchwork, purrr, recipes, rsample, tibble, tidyr, tidyselect, tune, workflows, yardstick, flashlight, future.apply, MetricsWeighted, finetune, hstats Suggests: knitr, rmarkdown, testthat (>= 3.0.0), ape, vegan, hardhat, ggrepel, themis, MRFcov, lme4, randomForest, ggnetwork, igraph, tidymodels, tidyverse, parsnip, gridExtra, future, generics, missForest, kernelshap, shapviz Nick Fountain-Jones <nick.fountainjones@utas.edu.au> Comprehensive R Archive Network (CRAN) Nick Fountain-Jones [aut, cre, cph] (ORCID: <https://orcid.org/0000-0001-9248-8493>), Ryan Leadbetter [aut] (ORCID: <https://orcid.org/0000-0002-1942-3121>), Gustavo Machado [aut] (ORCID: <https://orcid.org/0000-0001-7552-6144>), Chris Kozakiewicz [aut], Nick Clark [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=mrIML/LICENSE) 2025-11-21 application/tgz https://CRAN.R-project.org/package=mrIML doi:10.32614/CRAN.package.mrIML