{ "_id": "6a10aac8acfb0bcc41cbf238", "Package": "vip", "Type": "Package", "Title": "Variable Importance Plots", "Version": "0.4.6", "Authors@R": "c(\nperson(c(\"Brandon\", \"M.\"), family = \"Greenwell\",\nemail = \"greenwell.brandon@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-8120-0084\")),\nperson(\"Brad\", \"Boehmke\",\nemail = \"bradleyboehmke@gmail.com\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0002-3611-8516\"))\n)", "Description": "A general framework for constructing variable importance\nplots from various types of machine learning models in R. Aside\nfrom some standard model- specific variable importance\nmeasures, this package also provides model- agnostic approaches\nthat can be applied to any supervised learning algorithm. These\ninclude 1) an efficient permutation-based variable importance\nmeasure, 2) variable importance based on Shapley values\n(Strumbelj and Kononenko, 2014)\n, and 3) the variance-based\napproach described in Greenwell et al. (2018)\n. A variance-based method for\nquantifying the relative strength of interaction effects is\nalso included (see the previous reference for details).", "License": "GPL (>= 2)", "URL": "https://github.com/koalaverse/vip/,\nhttps://koalaverse.github.io/vip/", "BugReports": "https://github.com/koalaverse/vip/issues", "Encoding": "UTF-8", "VignetteBuilder": "knitr", "RoxygenNote": "7.3.3", "Roxygen": "list(markdown = TRUE)", "Repository": "https://koalaverse.r-universe.dev", "Date/Publication": "2026-04-22 01:15:09 UTC", "RemoteUrl": "https://github.com/koalaverse/vip", "RemoteRef": "HEAD", "RemoteSha": "c5b90e78c64adc440f6742f69d364c3a711e10e1", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-22 18:50:44 UTC", "User": "root" }, "Author": "Brandon M. Greenwell [aut, cre] (ORCID:\n),\nBrad Boehmke [aut] (ORCID: )", "Maintainer": "Brandon M. 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Greenwell", "email": "greenwell.brandon@gmail.com", "login": "bgreenwell", "twitter": "@bgreenwell8", "description": "Director, Data Science at 84.51° and Adjunct Instructor at the University of Cincinnati.", "uuid": 3777755, "orcid": "0000-0002-8120-0084" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.1.0", "role": "Depends" }, { "package": "foreach", "role": "Imports" }, { "package": "ggplot2", "version": ">= 0.9.0", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "tibble", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "yardstick", "role": "Imports" }, { "package": "bookdown", "role": "Suggests" }, { "package": "DT", "role": "Suggests" }, { "package": "covr", "role": "Suggests" }, { "package": "doParallel", "role": "Suggests" }, { "package": "dplyr", "role": "Suggests" }, { "package": "fastshap", "version": ">= 0.1.0", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { 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