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Weak supervision
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Paradigm in machine learning
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Wikipedia

Weak supervision (also known as semi-supervised learning) is a paradigm in machine learning, the relevance and notability of which increased with the advent of large language models due to the large amount of data required to train them. It is characterized by using a combination of a small amount of human-labeled data (exclusively used in more...

Subclass of
Supervised learning
References
Wikidata