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 ORCID iD [aut, cre]
Maintainer: Enrique Garcia-Ceja < at>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: ssr results


Reference manual: ssr.pdf
Vignettes: Introduction to the ssr package


Package source: ssr_0.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


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