Semi-Supervised Regression Methods R package ssr version 0.1.1 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. Software Depends: R (>= 3.6.0) Imports: caret, e1071 Suggests: knitr, rmarkdown, tgp Enrique Garcia-Ceja <e.g.mx@ieee.org> Comprehensive R Archive Network (CRAN) Enrique Garcia-Ceja [aut, cre] (ORCID: <https://orcid.org/0000-0001-6864-8557>) GPL-3 2019-09-02 application/tgz https://CRAN.R-project.org/package=ssr doi:10.32614/CRAN.package.ssr