Parametric non-parallel support vector machines for pattern classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s10994-022-06238-0.pdf
Reference29 articles.
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2. Chen, W. J., Shao, Y. H., Li, C. N., et al. (2020). $$\nu$$-projection twin support vector machine for pattern classification. Neurocomputing, 376, 10–24.
3. Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine learning, 20(3), 273–297.
4. Diethe, T. (2015). 13 benchmark datasets derived from the UCI, DELVE and STATLOG repositories. https://github.com/tdiethe/gunnar_raetsch_benchmark_datasets/, https://doi.org/10.5281/zenodo.18110
5. Hao, L., & Lewin, P. (2010). Partial discharge source discrimination using a support vector machine. IEEE Transactions on Dielectrics and electrical Insulation, 17(1), 189–197.
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