AUC-Maximizing Ensembles through Metalearning
AUC-Maximizing Ensembles through Metalearning
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Full title
Author / Creator
Publisher
Germany: De Gruyter
Journal title
Language
English
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Publisher
Germany: De Gruyter
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Scope and Contents
Contents
Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maxi...
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Full title
AUC-Maximizing Ensembles through Metalearning
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4912128
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4912128
Other Identifiers
ISSN
2194-573X
E-ISSN
1557-4679
DOI
10.1515/ijb-2015-0035
