RSSL: Implementations of Semi-Supervised Learning Approaches for Classification

A collection of implementations of semi-supervised classifiers and methods to evaluate their performance. The package includes implementations of, among others, Implicitly Constrained Learning, Moment Constrained Learning, the Transductive SVM, Manifold regularization, Maximum Contrastive Pessimistic Likelihood estimation, S4VM and WellSVM.

Version: 0.9.7
Depends: R (≥ 2.10.0)
Imports: methods, Rcpp, MASS, kernlab, quadprog, Matrix, dplyr, tidyr, ggplot2, reshape2, scales, cluster
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, rmarkdown, SparseM, numDeriv, LiblineaR, covr
Published: 2023-12-07
DOI: 10.32614/CRAN.package.RSSL
Author: Jesse Krijthe [aut, cre]
Maintainer: Jesse Krijthe <jkrijthe at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: RSSL citation info
Materials: README
CRAN checks: RSSL results


Reference manual: RSSL.pdf


Package source: RSSL_0.9.7.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): RSSL_0.9.7.tgz, r-oldrel (arm64): RSSL_0.9.7.tgz, r-release (x86_64): RSSL_0.9.7.tgz, r-oldrel (x86_64): RSSL_0.9.7.tgz
Old sources: RSSL archive

Reverse dependencies:

Reverse imports: SSLR


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