Implementations of Semi-Supervised Learning Approaches for Classification
Throw out labels at random
Calculate knn adjacency matrix
Classifier used for enabling shared documenting of parameters
Merge result of cross-validation runs on single datasets into a the sa...
Use mclapply conditional on not being in RStudio
Biased (maximum likelihood) estimate of the covariance matrix
Cross-validation in semi-supervised setting
Decision values returned by a classifier for a set of objects
Convert data.frame with missing labels to matrices
An Expectation Maximization like approach to Semi-Supervised Least Squ...
Semi-Supervised Linear Discriminant Analysis using Expectation Maximiz...
Semi-Supervised Nearest Mean Classifier using Expectation Maximization
Entropy Regularized Logistic Regression
Performance measures used in classifier evaluation
Find a violated label
calculated the gaussian kernel matrix
Generate data from 2 Gaussian distributed classes
Generate data from 2 alternating classes
Generate Crescent Moon dataset
Generate Four Clusters dataset
Generate Parallel planes
Generate Sliced Cookie dataset
Generate Intersecting Spirals
Generate data from 2 circles
Plot RSSL classifier boundary (deprecated)
Plot linear RSSL classifier boundary
Label propagation using Gaussian Random Fields and Harmonic functions
Direct R Translation of Xiaojin Zhu's Matlab code to determine harmoni...
Implicitly Constrained Least Squares Classifier
Implicitly Constrained Semi-supervised Linear Discriminant Classifier
Kernelized Implicitly Constrained Least Squares Classification
Kernelized Least Squares Classifier
Laplacian Regularized Least Squares Classifier
Laplacian SVM classifier
Compute Semi-Supervised Learning Curve
Least Squares Classifier
Loss of a classifier or regression function
Linear Discriminant Classifier
LinearSVM Class
Linear SVM Classifier
Linear CCCP Transductive SVM classifier
Local descent
LogisticLossClassifier
Logistic Loss Classifier
(Regularized) Logistic Regression implementation
Logistic Regression implementation that uses R's glm
Numerically more stable way to calculate log sum exp
Loss of a classifier or regression function
LogsumLoss of a classifier or regression function
Loss of a classifier or regression function evaluated on partial label...
Majority Class Classifier
Moment Constrained Semi-supervised Linear Discriminant Analysis.
Moment Constrained Semi-supervised Nearest Mean Classifier
Maximum Contrastive Pessimistic Likelihood Estimation for Linear Discr...
Implements weighted likelihood estimation for LDA
Access the true labels for the objects with missing labels when they a...
Nearest Mean Classifier
Plot CrossValidation object
Plot LearningCurve object
Class Posteriors of a classifier
Predict for matrix scaling inspired by stdize from the PLS package
Preprocess the input to a classification function
Preprocess the input for a new set of test objects for classifier
Print CrossValidation object
Print LearningCurve object
Project an n-dim vector y to the simplex Dn
Quadratic Discriminant Classifier
Responsibilities assigned to the unlabeled objects
Show RSSL classifier
RSSL: Implementations of Semi-Supervised Learning Approaches for Class...
Predict using RSSL classifier
LinearSVM Class
Safe Semi-supervised Support Vector Machine (S4VM)
Sample k indices per levels from a factor
Matrix centering and scaling
Self-Learning approach to Semi-supervised Learning
SVM solve.QP implementation
Create Train, Test and Unlabeled Set
Randomly split dataset in multiple parts
Convert data.frame to matrices for semi-supervised learners
Plot RSSL classifier boundaries
Calculate the standard error of the mean from a vector of numbers
Summary of Crossvalidation results
Inverse of a matrix using the singular value decomposition
Taking the inverse of the square root of the matrix using the singular...
Taking the square root of a matrix using the singular value decomposit...
SVM Classifier
svmlin implementation by Sindhwani & Keerthi (2006)
Train SVM
Refine the prediction to satisfy the balance constraint
Access the true labels when they are stored as an attribute in a data ...
Transductive SVM classifier using the convex concave procedure
USMLeastSquaresClassifier
Updated Second Moment Least Squares Classifier
wellsvm implements the wellsvm algorithm as shown in [1].
Convex relaxation of S3VM by label generation
A degenerated version of WellSVM where the labels are complete, that i...
WellSVM for Semi-supervised Learning
Measures the expected error of the LDA model defined by m, p, and iW o...
Measures the expected log-likelihood of the LDA model defined by m, p,...
Implements weighted likelihood estimation for LDA
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.