mlsanityData to 7 Oct 2026

Survey of resampling techniques for improving classification performance in unbalanced datasets

arXiv 1608.06048 ↗First posted 22 Aug 2016stat.AP cs.LG stat.MLcited by 32

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Abstract (arXiv)

A number of classification problems need to deal with data imbalance between classes. Often it is desired to have a high recall on the minority class while maintaining a high precision on the majority class. In this paper, we review a number of resampling techniques proposed in literature to handle unbalanced datasets and study their effect on classification performance.

Key facts. Cited by 32 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Aug 2016.

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Citing papers per year: 2021: 7; 2022: 12; 2023: 6; 2024: 3; 2025: 3; 2026: 1.

32 papers.

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  1. 2022Language-Grounded Indoor 3D Semantic Segmentation in the Wildcited by 243
  2. 2021GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networkscited by 147
  3. 2021Contrastive Learning based Hybrid Networks for Long-Tailed Image Classificationcited by 130
  4. 2021GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Predictioncited by 36
  5. 2024TabPFGen -- Tabular Data Generation with TabPFNcited by 26
  6. 2022Towards Automated Imbalanced Learning with Deep Hierarchical Reinforcement Learningcited by 9
  7. 2023Uncertainty-guided Boundary Learning for Imbalanced Social Event Detectioncited by 8
  8. 2024Machine Learning Robustness: A Primercited by 8
  9. 2021Constrained Differentially Private Federated Learning for Low-bandwidth Devicescited by 6
  10. 2022Synthetic Over-sampling for Imbalanced Node Classification with Graph Neural Networkscited by 6
  11. 2022Effective Class-Imbalance learning based on SMOTE and Convolutional Neural Networkscited by 6
  12. 2023SC-MIL: Supervised Contrastive Multiple Instance Learning for Imbalanced Classification in Pathologycited by 5
20 more
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  3. 2021Selecting the suitable resampling strategy for imbalanced data classification regarding dataset propertiescited by 2
  4. 2022Testing Feedforward Neural Networks Training Programscited by 2
  5. 2022Domain-Aware Contrastive Knowledge Transfer for Multi-domain Imbalanced Datacited by 2
  6. 2022Combating Noisy Labels in Long-Tailed Image Classificationcited by 2
  7. 2021Deep Representation of Imbalanced Spatio-temporal Traffic Flow Data for Traffic Accident Detectioncited by 1
  8. 2022Supervised Contrastive Learning on Blended Images for Long-tailed Recognitioncited by 1
  9. 2023Ensemble Modeling for Multimodal Visual Action Recognitioncited by 1
  10. 2023A Review of Machine Learning Techniques in Imbalanced Data and Future Trendscited by 1
  11. 2025Studying Illustrations in Manuscripts: An Efficient Deep-Learning Approachcited by 1
  12. 2021Graph-based Ensemble Machine Learning for Student Performance Predictioncited by 0
  13. 2022Job Offers Classifier using Neural Networks and Oversampling Methodscited by 0
  14. 2022Joint Debiased Representation and Image Clustering Learning with Self-Supervisioncited by 0
  15. 2023A dual-branch model with inter- and intra-branch contrastive loss for long-tailed recognitioncited by 0
  16. 2023COOL: A Constraint Object-Oriented Logic Programming Language and its Neural-Symbolic Compilation Systemcited by 0
  17. 2024Efficient Classification of Histopathology Imagescited by 0
  18. 2025Emotion estimation from video footage with LSTMcited by 0
  19. 2025On the Burstiness of Faces in Setcited by 0
  20. 2026Resolving Primitive-Sharing Ambiguity in Long-Tailed TLS-Based Industrial MEP Point Cloud Segmentation via Spatial Context Constraintscited by 0