Type: Package Package: iml Title: Interpretable Machine Learning Version: 0.11.4 Authors@R: c( person("Giuseppe", "Casalicchio", , "giuseppe.casalicchio@lmu.de", role = c("aut", "cre")), person("Christoph", "Molnar", , "christoph.molnar@gmail.com", role = c("aut")), person("Patrick", "Schratz", , "patrick.schratz@gmail.com", role = "aut", comment = c(ORCID = "0000-0003-0748-6624")) ) Maintainer: Giuseppe Casalicchio Description: Interpretability methods to analyze the behavior and predictions of any machine learning model. Implemented methods are: Feature importance described by Fisher et al. (2018) , accumulated local effects plots described by Apley (2018) , partial dependence plots described by Friedman (2001) , individual conditional expectation ('ice') plots described by Goldstein et al. (2013) , local models (variant of 'lime') described by Ribeiro et. al (2016) , the Shapley Value described by Strumbelj et. al (2014) , feature interactions described by Friedman et. al and tree surrogate models. License: MIT + file LICENSE URL: https://giuseppec.github.io/iml/, https://github.com/giuseppec/iml/ BugReports: https://github.com/giuseppec/iml/issues 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 VignetteBuilder: knitr Config/testthat/edition: 3 Config/testthat/parallel: true Encoding: UTF-8 Roxygen: list(markdown = TRUE, r6 = TRUE) RoxygenNote: 7.3.2 Repository: https://giuseppec.r-universe.dev Date/Publication: 2025-02-24 12:15:23 UTC RemoteUrl: https://github.com/giuseppec/iml RemoteRef: HEAD RemoteSha: 4818c8f81dea2e76318857fbc3d50bc78cdd22f6 NeedsCompilation: no Packaged: 2026-06-16 08:32:24 UTC; root Author: Giuseppe Casalicchio [aut, cre], Christoph Molnar [aut], Patrick Schratz [aut] (ORCID: )