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RSSL  

Implementations of Semi-Supervised Learning Approaches for Classification
View on CRAN: Click here


Download and install RSSL package within the R console
Install from CRAN:
install.packages("RSSL")

Install from Github:
library("remotes")
install_github("cran/RSSL")

Install by package version:
library("remotes")
install_version("RSSL", "0.9.8")



Attach the package and use:
library("RSSL")
Maintained by
Jesse Krijthe
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-09-15
Latest Update: 2023-12-07
Description:
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.
How to cite:
Jesse Krijthe (2016). RSSL: Implementations of Semi-Supervised Learning Approaches for Classification. R package version 0.9.8, https://cran.r-project.org/web/packages/RSSL. Accessed 07 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:20), 0.6.1 (2016-10-06 19:13), 0.6 (2016-09-15 00:24), 0.7 (2018-07-12 12:10), 0.8 (2019-03-08 19:42), 0.9.1 (2020-02-04 11:20), 0.9.2 (2020-09-12 07:50), 0.9.3 (2020-11-13 19:00), 0.9.5 (2022-01-17 16:12), 0.9.6 (2023-03-14 09:40), 0.9.7 (2023-12-07 07:20)
Other packages that cited RSSL R package
View RSSL citation profile
Other R packages that RSSL depends, imports, suggests or enhances
Complete documentation for RSSL
Functions, R codes and Examples using the RSSL R package
Some associated functions: BaseClassifier . CrossValidationSSL . EMLeastSquaresClassifier . EMLinearDiscriminantClassifier . EMNearestMeanClassifier . EntropyRegularizedLogisticRegression . GRFClassifier . ICLeastSquaresClassifier . ICLinearDiscriminantClassifier . KernelICLeastSquaresClassifier . KernelLeastSquaresClassifier . LaplacianKernelLeastSquaresClassifier . LaplacianSVM . LearningCurveSSL . LeastSquaresClassifier . LinearDiscriminantClassifier . LinearSVM-class . LinearSVM . LinearTSVM . LogisticLossClassifier-class . LogisticLossClassifier . LogisticRegression . LogisticRegressionFast . MCLinearDiscriminantClassifier . MCNearestMeanClassifier . MCPLDA . MajorityClassClassifier . NearestMeanClassifier . PreProcessing . PreProcessingPredict . QuadraticDiscriminantClassifier . RSSL . S4VM-class . S4VM . SSLDataFrameToMatrices . SVM . SelfLearning . TSVM . USMLeastSquaresClassifier-class . USMLeastSquaresClassifier . WellSVM . WellSVM_SSL . WellSVM_supervised . add_missinglabels_mar . adjacency_knn . c.CrossValidation . clapply . cov_ml . decisionvalues-methods . df_to_matrices . diabetes . evaluation-measures . find_a_violated_label . gaussian_kernel . generate2ClassGaussian . generateABA . generateCrescentMoon . generateFourClusters . generateParallelPlanes . generateSlicedCookie . generateSpirals . generateTwoCircles . geom_classifier . geom_linearclassifier . harmonic_function . line_coefficients-methods . localDescent . logsumexp . loss-methods . losslogsum-methods . losspart-methods . minimaxlda . missing_labels . plot.CrossValidation . plot.LearningCurve . posterior-methods . predict-scaleMatrix-method . print.CrossValidation . print.LearningCurve . projection_simplex . responsibilities-methods . rssl-formatting . rssl-predict . sample_k_per_level . scaleMatrix . solve_svm . split_dataset_ssl . split_random . stat_classifier . stderror . summary.CrossValidation . svdinv . svdinvsqrtm . svdsqrtm . svmlin . svmlin_example . svmproblem . testdata . threshold . true_labels . wdbc . wellsvm_direct . wlda . wlda_error . wlda_loglik . 
Some associated R codes: Classifier.R . CrossValidation.R . EMLeastSquaresClassifier.R . EMLinearDiscriminantClassifier.R . EMNearestMeanClassifier.R . EntropyRegularizedLogisticRegression.R . Evaluate.R . GRFClassifier.R . GenerateSSLData.R . Generics.R . HelperFunctions.R . ICLeastSquaresClassifier.R . ICLinearDiscriminantClassifier.R . KernelICLeastSquaresClassifier.R . KernelLeastSquaresClassifier.R . LaplacianKernelLeastSquaresClassifier.R . LaplacianSVM.R . LearningCurve.R . LeastSquaresClassifier.R . LinearDiscriminantClassifier.R . LinearSVM.R . LogisticLossClassifier.R . LogisticRegression.R . MCLinearDiscriminantClassifier.R . MCNearestMeanClassifier.R . MCPLDA.R . MajorityClassClassifier.R . Measures.R . NearestMeanClassifier.R . NormalBasedClassifier.R . Plotting.R . QuadraticDiscriminantClassifier.R . RSSL.R . RcppExports.R . S4VM.R . SVM.R . SelfLearning.R . TSVM.R . USMLeastSquaresClassifier.R . WellSVM.R . scaleMatrix.R . svmd.R . svmlin.R . testdata-data.R .  Full RSSL package functions and examples
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