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Sankore

Named after the University of Sankore in Timbuktu — one of the world’s oldest centres of learning. Every figure here is computed from work-level records in our own graph, never copied from a source’s summary count.

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Coverage is partial and says so. A country appears with its research output only once its works have been swept; until then the portal shows whatever the graph happens to hold for it and labels it as exactly that.

COMPARATIVE PERFORMANCE OF MACHINE LEARNING MODELS FOR CREDIT CARD FRAUD DETECTION ON IMBALANCED DATA: A STUDY USING SMOTE AND THE KAGGLE EUROPEAN DATASET

2026FUDMA Journal of SciencesJournalOpen access

10.33003/fjs-2026-1003-4745 Full text1 citations

Authors

4 authors.

Opeyemi Femi OjoFirst author
- Federal University Lokoja (NG)
Paul Olawale Otaru
- Federal University Lokoja (NG)
Eunice O.Job
- Federal University Lokoja (NG)
Benson OnoghojobiSenior author
- Federal University Lokoja (NG)

Fields

Assignment is probabilistic — a work belongs to several fields in proportions.

Imbalanced Data Classification Techniqueslevel 3 · 0.93
Financial Distress and Bankruptcy Predictionlevel 3 · 0.05
Explainable Artificial Intelligence (XAI)level 3 · 0.00

Sources

Several sources describing one work is the point — it means the record rests on more than one authority.

openalexseen September 9, 2026
2026 · FUDMA Journal of Sciences · 1 citations
https://openalex.org/W7138968447

COMPARATIVE PERFORMANCE OF MACHINE LEARNING MODELS FOR CREDIT CARD FRAUD DETECTION ON IMBALANCED DATA: A STUDY USING SMOTE AND THE KAGGLE EUROPEAN DATASET · Sankore