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>.
| Version: | 2.2.0 |
| 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 |
| Published: | 2025-11-21 |
| DOI: | 10.32614/CRAN.package.mrIML |
| Author: | Nick Fountain-Jones [aut, cre, cph], Ryan Leadbetter [aut], Gustavo Machado [aut], Chris Kozakiewicz [aut], Nick Clark [aut] |
| Maintainer: | Nick Fountain-Jones <nick.fountainjones at utas.edu.au> |
| BugReports: | https://github.com/nickfountainjones/mrIML/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/nickfountainjones/mrIML |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| CRAN checks: | mrIML results |