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News/RUBRIC: Realism--Utility Balanced Ranking for Imbalanced Classification
arxiv
PublishedJuly 22, 2026 at 4:00 AM
—neutral

RUBRIC: Realism--Utility Balanced Ranking for Imbalanced Classification

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Publisher summary· verbatim

arXiv:2607.09816v2 Announce Type: replace Abstract: Class imbalance poses a fundamental challenge in risk-sensitive applications such as fraud detection and medical diagnosis, where minority-class samples are scarce yet critical for accurate classification. Existing oversampling methods generate syn

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#class-imbalance#oversampling#fraud-detection#machine-learning

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Source
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arxiv
Read original ↗All from arxiv →
Tags
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#class-imbalance#oversampling#fraud-detection#machine-learning

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