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s2net: The Generalized Semi-Supervised Elastic-Net

Implements the generalized semi-supervised elastic-net. This method extends the supervised elastic-net problem, and thus it is a practical solution to the problem of feature selection in semi-supervised contexts. Its mathematical formulation is presented from a general perspective, covering a wide range of models. We focus on linear and logistic responses, but the implementation could be easily extended to other losses in generalized linear models. We develop a flexible and fast implementation, written in 'C++' using 'RcppArmadillo' and integrated into R via 'Rcpp' modules. See Culp, M. 2013 <doi:10.1080/10618600.2012.657139> for references on the Joint Trained Elastic-Net.

Version: 1.0.7
Depends: stats
Imports: Rcpp, methods, MASS
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, glmnet, Metrics, testthat
Published: 2024-03-31
Author: Juan C. Laria ORCID iD [aut, cre], Line H. Clemmensen [aut]
Maintainer: Juan C. Laria <juank.laria at gmail.com>
BugReports: https://github.com/jlaria/s2net/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/jlaria/s2net
NeedsCompilation: yes
Citation: s2net citation info
Materials: README
CRAN checks: s2net results

Documentation:

Reference manual: s2net.pdf
Vignettes: The supervised 's2net'

Downloads:

Package source: s2net_1.0.7.tar.gz
Windows binaries: r-devel: s2net_1.0.7.zip, r-release: s2net_1.0.7.zip, r-oldrel: s2net_1.0.7.zip
macOS binaries: r-release (arm64): s2net_1.0.7.tgz, r-oldrel (arm64): s2net_1.0.7.tgz, r-release (x86_64): s2net_1.0.7.tgz, r-oldrel (x86_64): s2net_1.0.7.tgz
Old sources: s2net archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=s2net to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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