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.

AuthorJunxiang Wang
Date of publication2016-05-14 23:12:09
MaintainerJunxiang Wang <xianggebenben@163.com>
LicenseGPL (>= 3)
Version0.1

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