ssr: Semi-Supervised Regression Methods
An implementation of semi-supervised regression methods including self-learning and co-training by committee based on Hady, M. F. A., Schwenker, F., & Palm, G. (2009) <doi:10.1007/978-3-642-04274-4_13>. Users can define which set of regressors to use as base models from the 'caret' package, other packages, or custom functions.
| Version: | 0.1.1 |
| Depends: | R (≥ 3.6.0) |
| Imports: | caret,e1071 |
| Suggests: | knitr,rmarkdown,tgp |
| Published: | 2019-09-02 |
| DOI: | 10.32614/CRAN.package.ssr |
| Author: | Enrique Garcia-Ceja [aut, cre] |
| Maintainer: | Enrique Garcia-Ceja <e.g.mx at ieee.org> |
| BugReports: | https://github.com/enriquegit/ssr/issues |
| License: | GPL-3 |
| URL: | https://github.com/enriquegit/ssr |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| CRAN checks: | ssr results |
Documentation:
| Reference manual: | ssr.html ,ssr.pdf |
| Vignettes: | Introduction to the ssr package (source,R code) |
Downloads:
| Package source: | ssr_0.1.1.tar.gz |
| Windows binaries: | r-devel:ssr_0.1.1.zip, r-release:ssr_0.1.1.zip, r-oldrel:ssr_0.1.1.zip |
| macOS binaries: | r-release (arm64):ssr_0.1.1.tgz, r-oldrel (arm64):ssr_0.1.1.tgz, r-release (x86_64):ssr_0.1.1.tgz, r-oldrel (x86_64):ssr_0.1.1.tgz |
| Old sources: | ssr archive |
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=ssrto link to this page.