An introduction to robust data analysis and its applications
Author:
Funder
Jan Evangelista Purkyně University in Ústí nad Labem
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10479-024-06167-2.pdf
Reference6 articles.
1. Jayadeva, Khemchandani, R., & Chandra, S. (2007). Twin support vector machines for pattern classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(5), 905–910.
2. Mangasarian, O. L., & Wild, E. W. (2005). Multisurface proximal support vector machine classification via generalized eigenvalues. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(1), 69–74.
3. Moosaei, H., & Hladík, M. (2023). Sparse solution of least-squares twin multi-class support vector machine using ℓ0 and ℓp-norm for classification and feature selection. Neural Networks, 166, 471–486.
4. Moosaei, H., Ketabchi, S., Razzaghi, S., & Tanveer, M. (2021). Generalized twin support vector machines. Neural Processing Letters, 53(2), 1545–1564.
5. Moosaei, H., Bazikar, F., & Hladík, M. (2024). Multi-task twin support vector machine with Universum data. Engineering Applications of Artificial Intelligence, 132, 107951.
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