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: 0.6.1
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
Published: 2016-10-06
Author: Jesse Krijthe [aut, cre]
Maintainer: Jesse Krijthe <jkrijthe at gmail.com>
BugReports: http://www.github.com/jkrijthe/RSSL
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.github.com/jkrijthe/RSSL
NeedsCompilation: yes
Citation: RSSL citation info
Materials: README
CRAN checks: RSSL results

Downloads:

Reference manual: RSSL.pdf
Package source: RSSL_0.6.1.tar.gz
Windows binaries: r-devel: RSSL_0.6.1.zip, r-release: RSSL_0.6.1.zip, r-oldrel: RSSL_0.6.1.zip
OS X Mavericks binaries: r-release: RSSL_0.6.1.tgz, r-oldrel: RSSL_0.6.1.tgz
Old sources: RSSL archive

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