Interpretability methods to analyze the behavior and predictions of any machine learning model. Implemented methods are: Feature importance described by Fisher et al. (2018) <doi:10.48550/arxiv.1801.01489>, accumulated local effects plots described by Apley (2018) <doi:10.48550/arxiv.1612.08468>, partial dependence plots described by Friedman (2001) <www.jstor.org/stable/2699986>, individual conditional expectation ('ice') plots described by Goldstein et al. (2013) <doi:10.1080/10618600.2014.907095>, local models (variant of 'lime') described by Ribeiro et. al (2016) <doi:10.48550/arXiv.1602.04938>, the Shapley Value described by Strumbelj et. al (2014) <doi:10.1007/s10115-013-0679-x>, feature interactions described by Friedman et. al <doi:10.1214/07-AOAS148> and tree surrogate models.
| Version: | 0.11.4 |
| Imports: | checkmate,data.table,Formula,future,future.apply,ggplot2,Metrics,R6 |
| Suggests: | ALEPlot,bench,bit64,caret,covr,e1071,future.callr,glmnet,gower,h2o,keras (≥ 2.2.5.0),knitr,MASS,mlr,mlr3,party,partykit,patchwork,randomForest,ranger,rmarkdown,rpart,testthat,yaImpute |
| Published: | 2025-02-24 |
| DOI: | 10.32614/CRAN.package.iml |
| Author: | Giuseppe Casalicchio [aut, cre], Christoph Molnar [aut], Patrick Schratz [aut] |
| Maintainer: | Giuseppe Casalicchio <giuseppe.casalicchio at lmu.de> |
| BugReports: | https://github.com/giuseppec/iml/issues |
| License: | MIT + fileLICENSE |
| URL: | https://giuseppec.github.io/iml/,https://github.com/giuseppec/iml/ |
| NeedsCompilation: | no |
| Citation: | iml citation info |
| Materials: | NEWS |
| In views: | MachineLearning |
| CRAN checks: | iml results |