{ "_id": "6ac2158e773a0037682c1a5b", "Package": "s2net", "Type": "Package", "Title": "The Generalized Semi-Supervised Elastic-Net", "Version": "1.0.5", "Date": "2024-03-04", "Authors@R": "c(person(\"Juan C.\",\n\"Laria\",,\nrole = c(\"aut\", \"cre\"),\nemail = \"juank.laria@gmail.com\",\ncomment = c(ORCID = \"0000-0001-7734-9647\")),\nperson(\"Line H.\",\n\"Clemmensen\",,\nrole = c(\"aut\"),\nemail = \"lkhc@dtu.dk\"))", "Description": "Implements the generalized semi-supervised elastic-net.\nThis method extends the supervised elastic-net problem, and\nthus it is a practical solution to the problem of feature\nselection in semi-supervised contexts. Its mathematical\nformulation is presented from a general perspective, covering a\nwide range of models. We focus on linear and logistic\nresponses, but the implementation could be easily extended to\nother losses in generalized linear models. We develop a\nflexible and fast implementation, written in 'C++' using\n'RcppArmadillo' and integrated into R via 'Rcpp' modules. See\nCulp, M. 2013 for references\non the Joint Trained Elastic-Net.", "License": "GPL (>= 2)", "VignetteBuilder": "knitr", "URL": "https://github.com/jlaria/s2net", "BugReports": "https://github.com/jlaria/s2net/issues", "Encoding": "UTF-8", "RoxygenNote": "7.2.0", "Repository": "https://jlaria.r-universe.dev", "Date/Publication": "2024-03-07 18:12:18 UTC", "RemoteUrl": "https://github.com/jlaria/s2net", "RemoteRef": "HEAD", "RemoteSha": "35e87106ebe32ce9c01f62801574284563998c69", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-10-04 08:44:37 UTC", "User": "root" }, "Author": "Juan C. Laria [aut, cre] (ORCID:\n),\nLine H. Clemmensen [aut]", "Maintainer": "Juan C. 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