Semi-supervised learning (machine learning)

Last revised by Daniel J Bell ◉ on 10 Mar 2020

Citation, DOI, disclosures and article data

Citation:

Moore C, Bell D, Semi-supervised learning (machine learning). Reference article, Radiopaedia.org (Accessed on 26 Sep 2023) https://doi.org/10.53347/rID-74943

DOI:

https://doi.org/10.53347/rID-74943

Permalink:

https://radiopaedia.org/articles/74943

rID:

74943

Article created:

10 Mar 2020, Candace Makeda Moore ◉

Disclosures:

At the time the article was created Candace Makeda Moore had no recorded disclosures.

View Candace Makeda Moore's current disclosures

Last revised:

10 Mar 2020, Daniel J Bell ◉

Disclosures:

At the time the article was last revised Daniel J Bell had no recorded disclosures.

View Daniel J Bell's current disclosures

Revisions:

2 times, by 2 contributors - see full revision history and disclosures

Sections:

Artificial Intelligence

Synonyms:

Semisupervised learning (machine learning)

Semi-supervised learning is an approach to machine learning which uses some labeled data and some data without labels to train models. This approach can be useful to overcome the problem of insufficient quantities of labeled data. Some consider it to be a variation of supervised learning, whilst other authors consider it to lie somewhere between supervised and unsupervised learning; however this categorization issue is academic. Such an approach has been applied to many types of problems including regression and classification problems.