{ "_id": "6a2e5c553efcd9bda430d10f", "Package": "DALEXtra", "Title": "Extension for 'DALEX' Package", "Version": "2.3.1", "Authors@R": "c(person(given = \"Szymon\",\nfamily = \"Maksymiuk\",\nrole = c(\"aut\", \"cre\"),\nemail = \"sz.maksymiuk@gmail.com\",\ncomment = c(ORCID = \"0000-0002-3120-1601\")),\nperson(given = \"Przemyslaw\",\nfamily = \"Biecek\",\nemail = \"przemyslaw.biecek@gmail.com\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0001-8423-1823\")),\nperson(\"Hubert\", \"Baniecki\", role = \"aut\"),\nperson(\"Anna\", \"Kozak\", role = \"ctb\"))", "Description": "Provides wrapper of various machine learning models. In\napplied machine learning, there is a strong belief that we need\nto strike a balance between interpretability and accuracy.\nHowever, in field of the interpretable machine learning, there\nare more and more new ideas for explaining black-box models,\nthat are implemented in 'R'. 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Important part\nof the package is Champion-Challenger analysis and innovative\napproach to model performance across subsets of test data\npresented in Funnel Plot.", "License": "GPL", "Encoding": "UTF-8", "RoxygenNote": "7.3.3", "URL": "https://ModelOriented.github.io/DALEXtra/,\nhttps://github.com/ModelOriented/DALEXtra", "BugReports": "https://github.com/ModelOriented/DALEXtra/issues", "Repository": "https://modeloriented.r-universe.dev", "Date/Publication": "2026-01-14 01:10:18 UTC", "RemoteUrl": "https://github.com/modeloriented/dalextra", "RemoteRef": "HEAD", "RemoteSha": "c8274a3e048c6e1cba23bf9d20cffb57e7216c4f", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-14 07:40:14 UTC", "User": "root" }, "Author": "Szymon Maksymiuk [aut, cre] (ORCID:\n),\nPrzemyslaw Biecek [aut] (ORCID:\n),\nHubert Baniecki [aut],\nAnna Kozak [ctb]", "Maintainer": "Szymon Maksymiuk ", "MD5sum": "fb7a2be1d0526a5aa3a6adb73ce3a778", "_user": "modeloriented", "_type": "src", "_file": 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