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Robust AUC optimization under the supervision of clean data

Robust AUC optimization under the supervision of clean data

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_7c17d9d21f284f6b86a9186518671936

Robust AUC optimization under the supervision of clean data

About this item

Full title

Robust AUC optimization under the supervision of clean data

Publisher

London: Nature Publishing Group UK

Journal title

Scientific reports, 2024-07, Vol.14 (1), p.16693-10, Article 16693

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

AUC (area under the ROC curve) is an essential metric that has been extensively researched in the field of machine learning. Traditional AUC optimization methods need a large-scale clean dataset, while real-world datasets usually contain massive noisy samples. To reduce the impact of noisy samples, many robust AUC optimization methods have been pro...

Alternative Titles

Full title

Robust AUC optimization under the supervision of clean data

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_7c17d9d21f284f6b86a9186518671936

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_7c17d9d21f284f6b86a9186518671936

Other Identifiers

ISSN

2045-2322

E-ISSN

2045-2322

DOI

10.1038/s41598-024-66788-2

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