Man pages for jkrijthe/RSSL
Implementations of Semi-Supervised Learning Approaches for Classification
| 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 gaussian 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 | Responsibilities assigned to the unlabeled objects |
| rssl-formatting | Show RSSL classifier |
| RSSL-package | RSSL: Implementations of Semi-Supervised Learning Approaches... |
| 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-supervised 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... |
