SSL: Semi-Supervised Learning

Semi-supervised learning has attracted the attention of machine learning community because of its high accuracy with less annotating effort compared with supervised learning.The question that semi-supervised learning wants to address is: given a relatively small labeled dataset and a large unlabeled dataset, how to design classification algorithms learning from both ? This package is a collection of some classical semi-supervised learning algorithms in the last few decades.

Getting started

Package details

AuthorJunxiang Wang
MaintainerJunxiang Wang <[email protected]>
LicenseGPL (>= 3)
Version0.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("SSL")

Try the SSL package in your browser

Any scripts or data that you put into this service are public.

SSL documentation built on May 29, 2017, 7:14 p.m.