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Weighted extreme learning machine for imbalance learning
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Cited by
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Wang, J., Lu, S., Wang, S.-H., & Zhang, Y.-D. (2022) · Multimedia Tools and Applications · doi:10.1007/s11042-021-11007-7 · Cited by 572
Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment
Jamshidi, M., Lalbakhsh, A., Talla, J., Peroutka, Z., Hadjilooei, F., Lalbakhsh, P., Jamshidi, M., Spada, L. L., Mirmozafari, M., Dehghani, M., et al. (2020) · IEEE Access · doi:10.1109/access.2020.3001973 · Cited by 551
Non-iterative and Fast Deep Learning: Multilayer Extreme Learning Machines
Zhang, J., Li, Y., Xiao, W., & Zhang, Z. (2020) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2020.04.033 · Cited by 179
Machine learning with a reject option: A survey
Hendrickx, K., Perini, L., Van der Plas, D., Meert, W., & Davis, J. (2024) · Machine Learning · doi:10.1007/s10994-024-06534-x · Cited by 134
Classification of BGP anomalies using decision trees and fuzzy rough sets
Li, Y., Xing, H.-J., Hua, Q., Wang, X.-Z., Batta, P., Haeri, S., & Trajkovic, L. (2014) · 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC) · doi:10.1109/smc.2014.6974096 · Cited by 36
Metadata
- Authors
- Zong, W., Huang, G.-B., & Chen, Y.
- Venue
- Neurocomputing
- Publisher
- Elsevier BV
- Published
- 2013-02
- Volume
- 101
- Pages
- 229-242
- ISSN
- 0925-2312 (ISSN-L)
- OpenAlex
- W2078622091
- Cited by
- 743
- References
- 0
- FWCI
- 29.45
- Type
- journal article
- Language
- en
- Open access
- closed
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How to cite
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- CoChat. (2026). Citation check: Weighted extreme learning machine for imbalance learning. https://app.cochat.ai/papers/10.1016/j.neucom.2012.08.010
- The paper
- Zong, W., Huang, G.-B., & Chen, Y. (2013). Weighted extreme learning machine for imbalance learning. Neurocomputing. https://doi.org/10.1016/j.neucom.2012.08.010
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.
