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: 1.0.1
Depends: stats
Imports: Rcpp, methods, MASS
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, glmnet, Metrics, testthat
Published: 2020-01-16
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


Reference manual: s2net.pdf
Vignettes: The supervised 's2net'
Package source: s2net_1.0.1.tar.gz
Windows binaries: r-devel: s2net_1.0.1.zip, r-devel-UCRT: s2net_1.0.1.zip, r-release: s2net_1.0.1.zip, r-oldrel: s2net_1.0.1.zip
macOS binaries: r-release (arm64): s2net_1.0.1.tgz, r-release (x86_64): s2net_1.0.1.tgz, r-oldrel: s2net_1.0.1.tgz
Old sources: s2net archive


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