Feature Importance Methods for Global Explanations R package xplainfi version 1.2.0 Provides a consistent interface for common feature importance methods as described in Ewald et al. (2024) <doi:10.1007/978-3-031-63797-1_22>, including permutation feature importance (PFI), conditional and relative feature importance (CFI, RFI), leave one covariate out (LOCO), and Shapley additive global importance (SAGE), as well as feature sampling mechanisms to support conditional importance methods. Software Depends: R (>= 4.1.0) Imports: checkmate, cli, data.table (>= 1.15.0), mirai, mlr3 (>= 1.1.0), mlr3fselect, mvtnorm, paradox (>= 1.0.0), R6, stats, utils Suggests: arf, DiagrammeR, foreach, future, future.apply, ggplot2, glue, gower, knitr, knockoff, lgr, mlr3data, mlr3learners, partykit, patchwork, ranger, rmarkdown, rpart, testthat (>= 3.0.0), withr Lukas Burk <cran@lukasburk.de> Comprehensive R Archive Network (CRAN) Lukas Burk [aut, cre, cph] (ORCID: <https://orcid.org/0000-0001-7528-3795>) LGPL (>= 3) 2026-07-24 application/tgz https://CRAN.R-project.org/package=xplainfi doi:10.32614/CRAN.package.xplainfi