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s2net
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
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-01-13
Latest Update: 2024-03-31
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 15 Jul. 2026.
Previous versions and publish date:
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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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