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s2net  

The Generalized Semi-Supervised Elastic-Net
View on CRAN: Click here


Download and install s2net package within the R console
Install from CRAN:
install.packages("s2net")

Install from Github:
library("remotes")
install_github("cran/s2net")

Install by package version:
library("remotes")
install_version("s2net", "1.0.7")



Attach the package and use:
library("s2net")
Maintained by
Juan C. Laria
[Scholar Profile | Author Map]
First Published: 2020-01-13
Latest Update: 2022-06-30
Description:
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 for references on the Joint Trained Elastic-Net.
How to cite:
Juan C. Laria (2020). s2net: The Generalized Semi-Supervised Elastic-Net. R package version 1.0.7, https://cran.r-project.org/web/packages/s2net. Accessed 22 Apr. 2025.
Previous versions and publish date:
1.0.1 (2020-01-16 14:20), 1.0.4 (2022-06-30 21:20), 1.0 (2020-01-13 18:10)
Other packages that cited s2net R package
View s2net citation profile
Other R packages that s2net depends, imports, suggests or enhances
Complete documentation for s2net
Functions, R codes and Examples using the s2net R package
Some associated functions: data_auto_mpg . predict.s2netR . predict_Rcpp_s2net . print_misc . s2Data . s2Fista . s2Params . s2net-class . s2netR . s2netRcpp-package . simulate_extra . simulate_groups . 
Some associated R codes: args.R . extJT.R . predict_Rcpp_s2net.R . s2Data.R . simulate.R . zzz.R .  Full s2net package functions and examples
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