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Research Article Peer ReviewedAt least two reviewers Open Access

Improving Computational Performance of Least Squares Multiple Birth Support Vector Machines with k-Means Clustering

1Kırıkkale University
✉ Corresponding author: Güvenç Arslan · guvenc.arslan@kku.edu.tr
Proceedings Cognitive Models and Artificial Intelligence Conference Volume 15 Pages 18–21 Year 2023
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References

  1. V. Vapnik and A. Chervonenkis, Theory of Pattern Recognition, Nauka, Moscow, 1974. G. Arslan, U. Madran, and D. Soyoğlu. “An Algebraic Approach to Clustering and Classification with Support Vector Machines,” Mathematics, 10.1: 128, Jan. 2022. Jayadeva, R. Khemchandani, and S. Chandra, “Twin Support Vector Machines for Pattern Classification”, IEEE Transactions on Pattern Analysis and Machine Intelligence., vol. 29 (5), pp. 905–910, May 2007. Z.-X. Yang, Y.-H. Shao, and X.-S Zhang, “Multiple birth support vector machine for multi-class classification” Neural Comput & Applic, 22 (Suppl 1), 153-161, 2013. doi: 10.1007/s00521-012-1108-x S.-G. Chen and X.-J Wu, “Multiple birth least squares support vector machine for multi-class classification” Int. J. Mach. Learn. & Cyber. 8, 1731-1742, 2017. doi: 10.1007/s13042-016-0554-7 J. Wang, X. Wu, and C. Zhang, “Support vector machines based on K-means clustering for real-time business intelligence systems”, International Journal of Business Intelligence and Data Mining, 1(1), 54-64, 2005. R. A. Fisher (1988) Iris. UCI Machine Learning Repository. https://doi.org/10.24432/C56C76. R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/ Dimitriadou, E.; Hornik, K.; Leisch, F.; Chang, C.-C.; Lin, C.-C. Package ‘e1071’. R Software Package. Available online: https://cran.r-project.org/web/packages/e1071 (accessed on 14 August 2021).

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Research Contributions (2019+)Peer reviewed by at least two reviewers
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