Funder
Science and Engineering Research Board
Publisher
Springer Science and Business Media LLC
Subject
Management Science and Operations Research,General Decision Sciences
Reference316 articles.
1. Agarwal, S., & Tomar, D. (2014). Siddhant: Prediction of software defects using twin support vector machine. In 2014 international conference on information systems and computer networks (ISCON) (pp. 128–132). IEEE.
2. Ai, Q., Wang, A., Zhang, A., Wang, Y., & Sun, H. (2018). A multi-class classification weighted least squares twin support vector hypersphere using local density information. IEEE Access, 6, 17284–17291.
3. Alam, S., Kwon, G.-R., Kim, J.-I., & Park, C.-S. (2017). Twin SVM-based classification of Alzheimer disease using complex dual-tree wavelet principal coefficients and LDA. Journal of Healthcare Engineering.
4. Ali, J., Aldhaifallah, M., Nisar, K. S., Aljabr, A., & Tanveer, M. (2022). Regularized least squares twin svm for multiclass classification. Big Data Research, 27, 100295.
5. Anand, P., Pandey, J.P., Rastogi, R., & Chandra, S. (2019). A privacy-preserving twin support vector machine classifier for vertical partitioned data. In Computational intelligence: Theories, applications and future directions (Vol. I, pp. 539–552). Springer.
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