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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.

Versions across snapshots

VersionRepositoryFileSize
1.0.7 rolling linux/jammy R-4.5 s2net_1.0.7.tar.gz 319.4 KiB
1.0.7 rolling linux/noble R-4.5 s2net_1.0.7.tar.gz 323.9 KiB
1.0.7 rolling source/ R- s2net_1.0.7.tar.gz 178.9 KiB
1.0.7 latest linux/jammy R-4.5 s2net_1.0.7.tar.gz 319.4 KiB
1.0.7 latest linux/noble R-4.5 s2net_1.0.7.tar.gz 323.9 KiB
1.0.7 latest source/ R- s2net_1.0.7.tar.gz 178.9 KiB
1.0.7 2026-04-26 source/ R- s2net_1.0.7.tar.gz 178.9 KiB
1.0.7 2026-04-23 source/ R- s2net_1.0.7.tar.gz 178.9 KiB
1.0.7 2026-04-09 windows/windows R-4.5 s2net_1.0.7.zip 729.9 KiB
1.0.7 2025-04-20 source/ R- s2net_1.0.7.tar.gz 178.9 KiB

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