The Generalized Semi-Supervised Elastic-Net R package s2net version 1.0.7 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. Software Depends: stats Imports: Rcpp, methods, MASS LinkingTo: Rcpp, RcppArmadillo Suggests: knitr, rmarkdown, glmnet, Metrics, testthat Juan C. Laria <juank.laria@gmail.com> Comprehensive R Archive Network (CRAN) Juan C. Laria [aut, cre] (ORCID: <https://orcid.org/0000-0001-7734-9647>), Line H. Clemmensen [aut] GPL (>= 2) 2024-03-31 application/tgz https://CRAN.R-project.org/package=s2net doi:10.32614/CRAN.package.s2net