SSL: Semi-Supervised Learning
Version 0.1

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
Date of publication2016-05-14 23:12:09
MaintainerJunxiang Wang <[email protected]>
LicenseGPL (>= 3)
Package repositoryView on CRAN
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SSL documentation built on May 29, 2017, 7:14 p.m.