A hybrid framework uses adaptive bin partitioning, CVAE, multistage oversampling, LDWL loss, and gated fusion to improve performance on imbalanced regression benchmarks.
, author Krawczyk, B
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
The study theoretically examines concept drift and evaluates drift detection algorithms across categories on diverse streaming datasets.
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Hybrid Imbalanced Regression Through Unified Data-Level and Algorithm-Level Balancing
A hybrid framework uses adaptive bin partitioning, CVAE, multistage oversampling, LDWL loss, and gated fusion to improve performance on imbalanced regression benchmarks.
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Learner-based Concept Drift Detection: Analysis and Evaluation
The study theoretically examines concept drift and evaluates drift detection algorithms across categories on diverse streaming datasets.