Applying explainable artificial intelligence to interpret supervised ensemble learning models for robust credit card fraud detection.
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| Title: | Applying explainable artificial intelligence to interpret supervised ensemble learning models for robust credit card fraud detection. |
|---|---|
| Authors: | Awad, Shimaa S.1 (AUTHOR) 2101391@eng.asu.edu.eg, Hamza, Alyaa A.2 (AUTHOR), Sobh, Mohamed A.1,2 (AUTHOR), Bahaa-Eldin, Ayman M.1 (AUTHOR) |
| Source: | Scientific Reports. 5/15/2026, Vol. 16 Issue 1, p1-47. 47p. |
| Database: | Academic Search Ultimate |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=193808955 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/s41598-026-49939-5 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 47 StartPage: 1 Titles: – TitleFull: Applying explainable artificial intelligence to interpret supervised ensemble learning models for robust credit card fraud detection. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Awad, Shimaa S. – PersonEntity: Name: NameFull: Hamza, Alyaa A. – PersonEntity: Name: NameFull: Sobh, Mohamed A. – PersonEntity: Name: NameFull: Bahaa-Eldin, Ayman M. IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 05 Text: 5/15/2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20452322 Numbering: – Type: volume Value: 16 – Type: issue Value: 1 Titles: – TitleFull: Scientific Reports Type: main |
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