The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets
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Citations
Cites
SMOTE synthetic minority over-sampling technique
Chawla, N. V., Bowyer, K. W., Hall, L. O., & Kegelmeyer, W. P. (2002) · Journal of Artificial Intelligence Research · doi:10.1613/jair.953 · Cited by 32,865
The class imbalance problem: A systematic study1
Japkowicz, N., & Stephen, S. (2002) · Intelligent Data Analysis · doi:10.3233/ida-2002-6504 · Cited by 3,295
Identifying Mislabeled Training Data
Brodley, C. E., & Friedl, M. A. (1999) · Journal of Artificial Intelligence Research · doi:10.1613/jair.606 · Cited by 612
Cited by
Learning from imbalanced data: open challenges and future directions
Krawczyk, B. (2016) · Progress in Artificial Intelligence · doi:10.1007/s13748-016-0094-0 · Cited by 2,459
Self-citationAbdullahi, M., Baashar, Y., Alhussian, H., Alwadain, A., Aziz, N., Capretz, L. F., & Abdulkadir, S. J. (2022) · Electronics · doi:10.3390/electronics11020198 · Cited by 361
A Systematic Study of Online Class Imbalance Learning With Concept Drift
Wang, S., Minku, L. L., & Yao, X. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2017.2771290 · Cited by 331
The class imbalance problem in deep learning
Ghosh, K., Bellinger, C., Corizzo, R., Branco, P., Krawczyk, B., & Japkowicz, N. (2024) · Machine Learning · doi:10.1007/s10994-022-06268-8 · Cited by 312
Self-citationGao, X., He, Y., Zhang, M., Diao, X., Jing, X., Ren, B., & Ji, W. (2021) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2020.104034 · Cited by 44
Metadata
- Authors
- Sáez, J. A., Krawczyk, B., & Woźniak, M.
- Venue
- Pattern Recognition
- Publisher
- Elsevier BV
- Published
- 2016-09
- Volume
- 57
- Pages
- 164-178
- ISSN
- 0031-3203 (ISSN-L)
- OpenAlex
- W2300921526
- Cited by
- 242
- References
- 3
- FWCI
- 21.58
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets. https://app.cochat.ai/papers/10.1016/j.patcog.2016.03.012
- The paper
- Sáez, J. A., Krawczyk, B., & Woźniak, M. (2016). Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets. Pattern Recognition. https://doi.org/10.1016/j.patcog.2016.03.012
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
