Package: s2net 1.0.7

Juan C. Laria

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.

Authors:Juan C. Laria [aut, cre], Line H. Clemmensen [aut]

s2net_1.0.7.tar.gz
s2net_1.0.7.tar.gz(r-4.5-noble)s2net_1.0.7.tar.gz(r-4.4-noble)
s2net_1.0.7.tgz(r-4.4-emscripten)s2net_1.0.7.tgz(r-4.3-emscripten)
s2net.pdf |s2net.html
s2net/json (API)

# Install 's2net' in R:
install.packages('s2net', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/jlaria/s2net/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

openblascppopenmp

2.70 score 7 scripts 125 downloads 13 exports 3 dependencies

Last updated 9 months agofrom:fa78f40a19. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 27 2024
R-4.5-linux-x86_64OKDec 27 2024

Exports:_rcpp_module_boot_Rcpp_s2net_exportpredictpredict_Rcpp_s2netpredict.s2netRprint.s2Dataprint.s2Fistas2Datas2Fistas2nets2netRs2Paramssimulate_extrasimulate_groups

Dependencies:MASSRcppRcppArmadillo

The supervised s2net

Rendered fromsupervised.Rmdusingknitr::rmarkdownon Dec 27 2024.

Last update: 2020-01-16
Started: 2020-01-13