RSSL: Implementations of Semi-Supervised Learning Approaches for Classification
Version 0.6.1

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.

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AuthorJesse Krijthe [aut, cre]
Date of publication2016-10-06 19:13:50
MaintainerJesse Krijthe <jkrijthe@gmail.com>
LicenseGPL (>= 2)
Version0.6.1
URL http://www.github.com/jkrijthe/RSSL
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("RSSL")

Man pages

add_missinglabels_mar: Throw out labels at random
adjacency_knn: Calculate knn adjacency matrix
BaseClassifier: Classifier used for enabling shared documenting of parameters
c.CrossValidation: Merge result of cross-validation runs on single datasets into...
clapply: Use mclapply conditional on not being in RStudio
cov_ml: Biased (maximum likelihood) estimate of the covariance matrix
CrossValidationSSL: Cross-validation in semi-supervised setting
decisionvalues-methods: Decision values returned by a classifier for a set of objects
df_to_matrices: Convert data.frame with missing labels to matrices
diabetes: diabetes data for unit testing
EMLeastSquaresClassifier: An Expectation Maximization like approach to Semi-Supervised...
EMLinearDiscriminantClassifier: Semi-Supervised Linear Discriminant Analysis using...
EMNearestMeanClassifier: Semi-Supervised Nearest Mean Classifier using Expectation...
EntropyRegularizedLogisticRegression: Entropy Regularized Logistic Regression
evaluation-measures: Performance measures used in classifier evaluation
find_a_violated_label: Find a violated label
gaussian_kernel: calculated the guassian kernel matrix
generate2ClassGaussian: Generate data from 2 Gaussian distributed classes
generateABA: Generate data from 2 alternating classes
generateCrescentMoon: Generate Crescent Moon dataset
generateFourClusters: Generate Four Clusters dataset
generateParallelPlanes: Generate Parallel planes
generateSlicedCookie: Generate Sliced Cookie dataset
generateSpirals: Generate Intersecting Spirals
generateTwoCircles: Generate data from 2 circles
geom_classifier: Plot RSSL classifier boundary (deprecated)
geom_linearclassifier: Plot linear RSSL classifier boundary
GRFClassifier: Label propagation using Gaussian Random Fields and Harmonic...
harmonic_function: Direct R Translation of Xiaojin Zhu's Matlab code to...
ICLeastSquaresClassifier: Implicitly Constrained Least Squares Classifier
ICLinearDiscriminantClassifier: Implicitly Constrained Semi-supervised Linear Discriminant...
KernelICLeastSquaresClassifier: Kernelized Implicitly Constrained Least Squares...
KernelLeastSquaresClassifier: Kernelized Least Squares Classifier
LaplacianKernelLeastSquaresClassifier: Laplacian Regularized Least Squares Classifier
LaplacianSVM: Laplacian SVM classifier
LearningCurveSSL: Compute Semi-Supervised Learning Curve
LeastSquaresClassifier: Least Squares Classifier
LinearDiscriminantClassifier: Linear Discriminant Classifier
LinearSVM: Linear SVM Classifier
LinearSVM-class: LinearSVM Class
LinearTSVM: Linear CCCP Transductive SVM classifier
line_coefficients-methods: Loss of a classifier or regression function
localDescent: Local descent
LogisticLossClassifier: Logistic Loss Classifier
LogisticLossClassifier-class: LogisticLossClassifier
LogisticRegression: (Regularized) Logistic Regression implementation
LogisticRegressionFast: Logistic Regression implementation that uses R's glm
logsumexp: Numerically more stable way to calculate log sum exp
losslogsum-methods: LogsumLoss of a classifier or regression function
loss-methods: Loss of a classifier or regression function
losspart-methods: Loss of a classifier or regression function evaluated on...
MajorityClassClassifier: Majority Class Classifier
MCLinearDiscriminantClassifier: Moment Constrained Semi-supervised Linear Discriminant...
MCNearestMeanClassifier: Moment Constrained Semi-supervised Nearest Mean Classifier
MCPLDA: Maximum Contrastive Pessimistic Likelihood Estimation for...
minimaxlda: Implements weighted likelihood estimation for LDA
missing_labels: Access the true labels for the objects with missing labels...
NearestMeanClassifier: Nearest Mean Classifier
plot.CrossValidation: Plot CrossValidation object
plot.LearningCurve: Plot LearningCurve object
posterior-methods: Class Posteriors of a classifier
predict-scaleMatrix-method: Predict for matrix scaling inspired by stdize from the PLS...
PreProcessing: Preprocess the input to a classification function
PreProcessingPredict: Preprocess the input for a new set of test objects for...
print.CrossValidation: Print CrossValidation object
print.LearningCurve: Print LearningCurve object
projection_simplex: project an n-dim vector y to the simplex Dn
QuadraticDiscriminantClassifier: Quadratic Discriminant Classifier
responsibilities-methods: Responsilibities assigned to the unlabeled objects
RSSL: R Semi-Supervised Learning Package
rssl-formatting: Show RSSL classifier
rssl-predict: Predict using RSSL classifier
S4VM: Safe Semi-supervised Support Vector Machine (S4VM)
S4VM-class: LinearSVM Class
sample_k_per_level: Sample k indices per levels from a factor
scaleMatrix: Matrix centering and scaling
SelfLearning: Self-Learning approach to Semi-supervised Learning
solve_svm: SVM solve.QP implementation
split_dataset_ssl: Create Train, Test and Unlabeled Set
split_random: Randomly split dataset in multiple parts
SSLDataFrameToMatrices: Convert data.frame to matrices for semi-supervised learners
stat_classifier: Plot RSSL classifier boundaries
stderror: Calculate the standard error of the mean from a vector of...
summary.CrossValidation: Summary of Crossvalidation results
svdinv: Inverse of a matrix using the singular value decomposition
svdinvsqrtm: Taking the inverse of the square root of the matrix using the...
svdsqrtm: Taking the square root of a matrix using the singular value...
SVM: SVM Classifier
svmlin: svmlin implementation by Sindhwani & Keerthi (2006)
svmlin_example: Test data from the svmlin implementation
svmproblem: Train SVM
testdata: Example semi-supervised problem
threshold: Refine the prediction to satisfy the balance constraint
true_labels: Access the true labels when they are stored as an attribute...
TSVM: Transductive SVM classifier using the convex concave...
USMLeastSquaresClassifier: Updated Second Moment Least Squares Classifier
USMLeastSquaresClassifier-class: USMLeastSquaresClassifier
wdbc: wdbc data for unit testing
WellSVM: WellSVM for Semi-superivsed Learning
wellsvm_direct: wellsvm implements the wellsvm algorithm as shown in [1].
WellSVM_SSL: Convex relaxation of S3VM by label generation
WellSVM_supervised: A degenerated version of WellSVM where the labels are...
wlda: Implements weighted likelihood estimation for LDA
wlda_error: Measures the expected error of the LDA model defined by m, p,...
wlda_loglik: Measures the expected log-likelihood of the LDA model defined...

Functions

BaseClassifier Man page Source code
CrossValidationSSL Man page Source code
CrossValidationSSL.list Man page Source code
CrossValidationSSL.matrix Man page Source code
EMLeastSquaresClassifier Man page Source code
EMLinearDiscriminantClassifier Man page Source code
EMNearestMeanClassifier Man page Source code
EntropyRegularizedLogisticRegression Man page Source code
GRFClassifier Man page Source code
ICLeastSquaresClassifier Man page Source code
ICLinearDiscriminantClassifier Man page Source code
KernelICLeastSquaresClassifier Man page Source code
KernelLeastSquaresClassifier Man page Source code
L_sl Source code
LaplacianKernelLeastSquaresClassifier Man page Source code
LaplacianSVM Man page Source code
LearningCurveSSL Man page Source code
LearningCurveSSL.list Source code
LearningCurveSSL.matrix Man page Source code
LeastSquaresClassifier Man page Source code
LinearDiscriminantClassifier Man page Source code
LinearSVM Man page Source code
LinearSVM-class Man page
LinearTSVM Man page Source code
LogisticLossClassifier Man page Source code
LogisticLossClassifier-class Man page
LogisticRegression Man page Source code
LogisticRegressionFast Man page Source code
MCLinearDiscriminantClassifier Man page Source code
MCNearestMeanClassifier Man page Source code
MCPLDA Man page Source code
MKL Source code
MajorityClassClassifier Man page Source code
NearestMeanClassifier Man page Source code
PreProcessing Man page Source code
PreProcessingPredict Man page Source code
QuadraticDiscriminantClassifier Man page Source code
RSSL Man page
RSSL-package Man page
S4VM Man page Source code
S4VM-class Man page
SSLDataFrameToMatrices Man page Source code
SVM Man page Source code
SelfLearning Man page Source code
TSVM Man page Source code
USMLeastSquaresClassifier Man page Source code
USMLeastSquaresClassifier-class Man page
WellSVM Man page Source code
WellSVM_SSL Man page Source code
WellSVM_supervised Man page Source code
add_missinglabels_mar Man page Source code
adjacency_knn Man page Source code
c.CrossValidation Man page Source code
clapply Man page Source code
classlabels_to_indicatormatrix Source code
coefficients_after_scaling Source code
cov_ml Man page Source code
decisionvalues Man page
decisionvalues,KernelLeastSquaresClassifier-method Man page
decisionvalues,LeastSquaresClassifier-method Man page
decisionvalues,LinearSVM-method Man page
decisionvalues,SVM-method Man page
decisionvalues,TSVM-method Man page
decisionvalues,WellSVM-method Man page
decisionvalues,svmlinClassifier-method Man page
df_to_matrices Man page Source code
diabetes Man page
factor_to_dummy Source code
factor_to_dummy_cpp Source code
find_a_violated_label Man page Source code
gaussian_kernel Man page Source code
generate2ClassGaussian Man page Source code
generateABA Man page Source code
generateCrescentMoon Man page Source code
generateFourClusters Man page Source code
generateParallelPlanes Man page Source code
generateSlicedCookie Man page Source code
generateSpirals Man page Source code
generateTwoCircles Man page Source code
generate_change_vector Source code
geom_classifier Man page Source code
geom_linearclassifier Man page Source code
grad_entropy Source code
grad_erlr Source code
grad_logistic Source code
grad_logisticregression Source code
grad_sl Source code
gradient_iclda Source code
gradient_kicls Source code
gradient_kicls_semi Source code
gradient_minmin_contrastive_ls Source code
gradient_minmin_lsq Source code
gradient_minmin_lsy Source code
harmonic_function Man page Source code
harmonic_function_cpp Source code
hs Source code
line_coefficients Man page
line_coefficients,LeastSquaresClassifier-method Man page
line_coefficients,LinearSVM-method Man page
line_coefficients,LogisticLossClassifier-method Man page
line_coefficients,LogisticRegression-method Man page
line_coefficients,NormalBasedClassifier-method Man page
line_coefficients,QuadraticDiscriminantClassifier-method Man page
line_coefficients,SelfLearning-method Man page
linearProgramming Source code
localDescent Man page Source code
logsumexp Man page Source code
loss Man page
loss,KernelLeastSquaresClassifier-method Man page
loss,LeastSquaresClassifier-method Man page
loss,LinearSVM-method Man page
loss,LogisticLossClassifier-method Man page
loss,LogisticRegression-method Man page
loss,MajorityClassClassifier-method Man page
loss,NormalBasedClassifier-method Man page
loss,SVM-method Man page
loss,SelfLearning-method Man page
loss,USMLeastSquaresClassifier-method Man page
loss,svmlinClassifier-method Man page
loss_entropy Source code
loss_erlr Source code
loss_iclda Source code
loss_logistic Source code
loss_logisticregression Source code
loss_minmin_contrastive_ls Source code
loss_minmin_lsq Source code
loss_minmin_lsy Source code
losslogsum Man page
losslogsum,NormalBasedClassifier-method Man page
losspart Man page
losspart,NormalBasedClassifier-method Man page
main_function Source code
measure_accuracy Man page Source code
measure_error Man page Source code
measure_losslab Man page Source code
measure_losstest Man page Source code
measure_losstrain Man page Source code
minimaxlda Man page Source code
missing_labels Man page Source code
objective_kicls Source code
objective_kicls_semi Source code
plot.CrossValidation Man page Source code
plot.LearningCurve Man page Source code
posterior Man page
posterior,NormalBasedClassifier-method Man page
predict,GRFClassifier-method Man page
predict,KernelLeastSquaresClassifier-method Man page
predict,LeastSquaresClassifier-method Man page
predict,LinearSVM-method Man page
predict,LogisticLossClassifier-method Man page
predict,LogisticRegression-method Man page
predict,MajorityClassClassifier-method Man page
predict,NormalBasedClassifier-method Man page
predict,SVM-method Man page
predict,SelfLearning-method Man page
predict,USMLeastSquaresClassifier-method Man page
predict,WellSVM-method Man page
predict,scaleMatrix-method Man page
predict,svmlinClassifier-method Man page
predict.svmd Source code
prediction_func Source code
print.CrossValidation Man page Source code
print.LearningCurve Man page Source code
projection_simplex Man page Source code
psi Source code
psi_grad Source code
responsibilities Man page
responsibilities,GRFClassifier-method Man page
rowMax Source code
rowwise_addition Source code
rssl-formatting Man page
rssl-predict Man page
sample_k_per_level Man page Source code
scaleMatrix Man page Source code
show,Classifier-method Man page
show,NormalBasedClassifier-method Man page
show,scaleMatrix-method Man page
solve_quadratic_bfgs Source code
solve_svm Man page Source code
sort_matrix Source code
split_dataset_ssl Man page Source code
split_random Man page Source code
squared_gradient Source code
squared_hessian Source code
squared_objective Source code
stat_classifier Man page Source code
stderror Man page Source code
summary.CrossValidation Man page Source code
svdeig Source code
svdinv Man page Source code
svdinvsqrtm Man page Source code
svdsqrtm Man page Source code
svm_opt_func Source code
svm_opt_grad Source code
svmd Source code
svmd.default Source code
svmd.formula Source code
svmlin Man page Source code
svmlin_example Man page
svmlin_rcpp Source code
svmproblem Man page Source code
testdata Man page
threshold Man page Source code
true_labels Man page Source code
tsvm_cccp_lin_gradient Source code
tsvm_cccp_lin_objective Source code
tsvm_lin_loss Source code
vec2vars Source code
wdbc Man page
wellsvm_direct Man page Source code
which_rowMax Source code
wlda Man page Source code
wlda_error Man page Source code
wlda_loglik Man page Source code

Files

inst
inst/examples
inst/examples/example-LaplacianKernelLeastSquaresClassifier.R
inst/examples/example-TSVM.R
inst/examples/example-GRFClassifier.R
inst/examples/example-WellSVM.R
inst/examples/example-LaplacianSVM.R
inst/examples/example-KernelLeastSquaresClassifier.R
inst/examples/example-S4VM.R
inst/examples/example-EntropyRegularizedLogisticRegression.R
inst/CITATION
inst/doc
inst/doc/SSL-Classifiers.Rmd
inst/doc/SSL-Classifiers.html
inst/doc/SSL-Classifiers.R
tests
tests/testthat.R
tests/testthat
tests/testthat/test-USMLeastSquaresClassifier.R
tests/testthat/test-S4VM.R
tests/testthat/test-GRFClassifier.R
tests/testthat/test-MCLinearDiscriminantClassifier.R
tests/testthat/test-LaplacianSVM.R
tests/testthat/test-SVM.R
tests/testthat/test-HelperFunctions.R
tests/testthat/test-MCPLDA.R
tests/testthat/test-ICLinearDiscriminantClassifier.R
tests/testthat/test-LeastSquaresClassifier.R
tests/testthat/test-LogisticLossClassifier.R
tests/testthat/test-EntropyRegularizedLogisticRegression.R
tests/testthat/test-QuadraticDiscriminantClassifier.R
tests/testthat/test-MCNearestMeanClassifier.R
tests/testthat/test-LearningCurves.R
tests/testthat/test-SelfLearning.R
tests/testthat/test-LaplacianKernelLeastSquaresClassifier.R
tests/testthat/test-LogisticRegression.R
tests/testthat/test-TSVM.R
tests/testthat/test-KernelLeastSquaresClassifier.R
tests/testthat/test-EMLeastSquaresClassifier.R
tests/testthat/test-EMNearestMeanClassifier.R
tests/testthat/test-svmlin.R
tests/testthat/test-ICLeastSquaresClassifier.R
tests/testthat/test-GenerateSSLData.R
tests/testthat/test-NearestMeanClassifier.R
tests/testthat/test-LinearDiscriminantClassifier.R
tests/testthat/test-KernelICLeastSquaresClassifier.R
tests/testthat/test-WellSVM.R
tests/testthat/test-CrossValidation.R
src
src/Makevars
src/GRFClassifier.cpp
src/svm.h
src/utils.cpp
src/Rsvm.c
src/svm.cpp
src/ssl.h
src/Makevars.win
src/RcppExports.cpp
src/ssl.cpp
src/svmlin_rcpp.cpp
NAMESPACE
data
data/diabetes.RData
data/wdbc.RData
data/testdata.RData
data/svmlin_example.RData
R
R/HelperFunctions.R
R/SVM.R
R/NormalBasedClassifier.R
R/SelfLearning.R
R/LaplacianSVM.R
R/EntropyRegularizedLogisticRegression.R
R/MCLinearDiscriminantClassifier.R
R/MCNearestMeanClassifier.R
R/GRFClassifier.R
R/LearningCurve.R
R/MCPLDA.R
R/CrossValidation.R
R/Evaluate.R
R/LaplacianKernelLeastSquaresClassifier.R
R/QuadraticDiscriminantClassifier.R
R/USMLeastSquaresClassifier.R
R/S4VM.R
R/WellSVM.R
R/LogisticRegression.R
R/svmlin.R
R/RSSL.R
R/TSVM.R
R/scaleMatrix.R
R/Measures.R
R/NearestMeanClassifier.R
R/LeastSquaresClassifier.R
R/GenerateSSLData.R
R/RcppExports.R
R/svmd.R
R/Plotting.R
R/LogisticLossClassifier.R
R/LinearDiscriminantClassifier.R
R/EMLeastSquaresClassifier.R
R/Classifier.R
R/KernelLeastSquaresClassifier.R
R/KernelICLeastSquaresClassifier.R
R/EMLinearDiscriminantClassifier.R
R/ICLinearDiscriminantClassifier.R
R/ICLeastSquaresClassifier.R
R/Generics.R
R/testdata-data.R
R/LinearSVM.R
R/MajorityClassClassifier.R
R/EMNearestMeanClassifier.R
README.md
MD5
DESCRIPTION
man
man/USMLeastSquaresClassifier.Rd
man/TSVM.Rd
man/LinearSVM.Rd
man/projection_simplex.Rd
man/EntropyRegularizedLogisticRegression.Rd
man/wellsvm_direct.Rd
man/rssl-formatting.Rd
man/USMLeastSquaresClassifier-class.Rd
man/sample_k_per_level.Rd
man/logsumexp.Rd
man/LogisticRegression.Rd
man/threshold.Rd
man/add_missinglabels_mar.Rd
man/wlda.Rd
man/generateABA.Rd
man/gaussian_kernel.Rd
man/geom_linearclassifier.Rd
man/CrossValidationSSL.Rd
man/generateCrescentMoon.Rd
man/PreProcessing.Rd
man/LearningCurveSSL.Rd
man/EMLinearDiscriminantClassifier.Rd
man/svmlin.Rd
man/LeastSquaresClassifier.Rd
man/adjacency_knn.Rd
man/KernelICLeastSquaresClassifier.Rd
man/MajorityClassClassifier.Rd
man/svdinv.Rd
man/stat_classifier.Rd
man/generateTwoCircles.Rd
man/MCLinearDiscriminantClassifier.Rd
man/missing_labels.Rd
man/NearestMeanClassifier.Rd
man/WellSVM_supervised.Rd
man/LogisticRegressionFast.Rd
man/wlda_loglik.Rd
man/harmonic_function.Rd
man/ICLinearDiscriminantClassifier.Rd
man/PreProcessingPredict.Rd
man/KernelLeastSquaresClassifier.Rd
man/posterior-methods.Rd
man/S4VM-class.Rd
man/svdinvsqrtm.Rd
man/MCNearestMeanClassifier.Rd
man/wdbc.Rd
man/predict-scaleMatrix-method.Rd
man/scaleMatrix.Rd
man/stderror.Rd
man/LinearSVM-class.Rd
man/summary.CrossValidation.Rd
man/svmproblem.Rd
man/ICLeastSquaresClassifier.Rd
man/solve_svm.Rd
man/minimaxlda.Rd
man/print.CrossValidation.Rd
man/true_labels.Rd
man/S4VM.Rd
man/print.LearningCurve.Rd
man/split_dataset_ssl.Rd
man/LinearDiscriminantClassifier.Rd
man/df_to_matrices.Rd
man/rssl-predict.Rd
man/responsibilities-methods.Rd
man/evaluation-measures.Rd
man/find_a_violated_label.Rd
man/plot.CrossValidation.Rd
man/losspart-methods.Rd
man/clapply.Rd
man/wlda_error.Rd
man/loss-methods.Rd
man/SVM.Rd
man/decisionvalues-methods.Rd
man/generateSlicedCookie.Rd
man/LogisticLossClassifier.Rd
man/EMLeastSquaresClassifier.Rd
man/geom_classifier.Rd
man/losslogsum-methods.Rd
man/QuadraticDiscriminantClassifier.Rd
man/BaseClassifier.Rd
man/localDescent.Rd
man/generate2ClassGaussian.Rd
man/testdata.Rd
man/EMNearestMeanClassifier.Rd
man/generateSpirals.Rd
man/LinearTSVM.Rd
man/GRFClassifier.Rd
man/plot.LearningCurve.Rd
man/line_coefficients-methods.Rd
man/svmlin_example.Rd
man/LaplacianSVM.Rd
man/LaplacianKernelLeastSquaresClassifier.Rd
man/RSSL.Rd
man/LogisticLossClassifier-class.Rd
man/diabetes.Rd
man/cov_ml.Rd
man/generateFourClusters.Rd
man/c.CrossValidation.Rd
man/WellSVM.Rd
man/SelfLearning.Rd
man/generateParallelPlanes.Rd
man/WellSVM_SSL.Rd
man/MCPLDA.Rd
man/svdsqrtm.Rd
man/split_random.Rd
man/SSLDataFrameToMatrices.Rd
RSSL documentation built on May 19, 2017, 4:42 p.m.