Weak supervision
Weak supervision is a branch of machine learning where noisy, limited, or imprecise sources are used to provide supervision signal for labeling large amounts of training data in a supervised learning setting. This approach alleviates the burden of obtaining hand-labeled data sets, which can be costly or impractical. Instead, inexpensive weak labels are employed with the understanding that they are imperfect, but can nonetheless be used to create a strong predictive model.Weak supervision is a generalization of semi-supervision, which is the historical approach to address the greediness of supervised learning in term of human annotations.
Wikipage redirect
Link from a Wikipage to another Wikipage
primaryTopic
Weak supervision
Weak supervision is a branch of machine learning where noisy, limited, or imprecise sources are used to provide supervision signal for labeling large amounts of training data in a supervised learning setting. This approach alleviates the burden of obtaining hand-labeled data sets, which can be costly or impractical. Instead, inexpensive weak labels are employed with the understanding that they are imperfect, but can nonetheless be used to create a strong predictive model.Weak supervision is a generalization of semi-supervision, which is the historical approach to address the greediness of supervised learning in term of human annotations.
has abstract
Weak supervision is a branch o ...... in term of human annotations.
@en
Wikipage page ID
60,968,880
page length (characters) of wiki page
Wikipage revision ID
1,023,854,513
Link from a Wikipage to another Wikipage
wikiPageUsesTemplate
subject
comment
Weak supervision is a branch o ...... in term of human annotations.
@en
label
Weak supervision
@en