{ "_id": "6ae37fef95ca2370cc8ce79d", "Package": "SWORD", "Type": "Package", "Title": "Support Vector Machine Weighted Oblique Random Decision Forests", "Version": "0.1.0", "Authors@R": "c(\nperson(\"Andrea\", \"Carta\", role = c(\"aut\", \"cre\"), email = \"andrea.carta88@unica.it\",\ncomment = c(ORCID = \"0000-0003-4077-1822\")),\nperson(\"Luca\", \"Frigau\", role = \"aut\"))", "Description": "Implements SWORD (Support vector machine Weighted Oblique\nRandom Decision forests), a random forest method for regression\nbased on TORS (Tree Oblique for Regression with weighted SVM)\noblique regression trees. At each internal node a Weighted-SVM\nclassifier with a linear kernel defines the oblique splitting\nhyperplane as a sparse linear combination of predictors. The\nC++ coordinate-descent solver provides fast training. Variable\nimportance is computed via OIW-VI (Oblique Impurity-Weighted\nVariable Importance). Provides tree fitting (TORS), forest\nfitting (SWORD), prediction, and variable importance\n(VI_SWORD). Parallel tree fitting is supported via the\n'future'/'furrr' framework. The SWORD method is described in\nCarta and Frigau (accepted, in press) 'Oblique Random Forests\nfor Regression via Weighted Support Vector Machine', Advances\nin Data Analysis and Classification. The TORS algorithm is\ndescribed in Carta and Frigau (2025)\n. The weighted SVM is based on\nYang, Song and Cao (2005) and\nthe 'WeightSVM' package by Xu et al. (2024)\n.", "License": "GPL-3", "URL": "https://github.com/acarta88/sword-package", "BugReports": "https://github.com/acarta88/sword-package/issues", "Encoding": "UTF-8", "VignetteBuilder": "knitr", "Config/roxygen2/version": "8.0.0", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-10-29 17:13:58 UTC", "User": "root" }, "Author": "Andrea Carta [aut, cre] (ORCID:\n), Luca Frigau [aut]", "Maintainer": "Andrea Carta ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-10-29 16:16:38 UTC", "RemoteUrl": "https://github.com/cran/SWORD", "RemoteRef": "HEAD", "RemoteSha": "1c58e0d9780f866df7e10046f990001fae11a7ed", "_user": "cran", "_type": "src", "_file": "SWORD_0.1.0.tar.gz", "_fileid": "https://r2.ropensci.org/7a505bcc268bdba20fe00b558914bf04f024a5bb48007bd0dcf379a3fc2dcd7f", "_filesize": 606432, "_sha256": "7a505bcc268bdba20fe00b558914bf04f024a5bb48007bd0dcf379a3fc2dcd7f", "_expires": "2027-02-06T17:18:37.000Z", "_created": "2026-10-29T17:13:58.000Z", 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