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: |
0.9.1 |
| 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: |
2020-02-04 |
| 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:
Reverse dependencies:
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