# RSSL: Semi-supervised Learning in R

arXiv: https://arxiv.org/abs/1612.07993 · HTML: https://mlsanity.com/paper/1612.07993/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Dec 2016.

## Built on by (most cited first, 2 of 2)

- [Self-Training of Halfspaces with Generalization Guarantees under Massart Mislabeling Noise Model](https://mlsanity.com/paper/2111.14427/) (2021)
- [Deep Low-Density Separation for Semi-Supervised Classification](https://mlsanity.com/paper/2205.11995/) (2022)

## Abstract (arXiv)

In this paper, we introduce a package for semi-supervised learning research in the R programming language called RSSL. We cover the purpose of the package, the methods it includes and comment on their use and implementation. We then show, using several code examples, how the package can be used to replicate well-known results from the semi-supervised learning literature.