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Research questionHow should imbalanced multi-label data be sampled to support rare-label inference while accounting for target frequencies and label dependencies?Rare labels may be underrepresented in ordinary samples, limiting reliable inference about them. Rebalancing their representation can also alter category frequencies and the relationships among labels that co-occur.
Machine Learning
Statistical Machine Learning
Latest papersRecent research connected to this question, newest first.A Multivariate Bernoulli-Based Sampling Method for Multi-Label Data with Application to Meta-ResearchApplies to multi-label datasets with observed label frequencies and dependencies, including Web of Science research articles assigned to 64 biomedical topic categories. Evidence covers subsamples from several datasets and focuses on balancing category representation while preserving frequency order and label dependencies.research paper · Sep 9, 2026
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