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Strong convergence of a modified extragradient algorithm to solve pseudomonotone equilibrium and application to classification of diabetes mellitus

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  • Cholamjiak, Watcharaporn
  • Suparatulatorn, Raweerote

Abstract

This work studies pseudomonotone equilibrium problems. The modified inertial viscosity subgradient extragradient is proposed for obtaining strong convergence, and it is proved under the assumption that the bifunction satisfies the Lipchitz-type condition. Flexible use of different stepsize parameters is offered. Moreover, the proposed algorithm is applied to solve diabetes mellitus classification problems. The algorithm’s efficiency is shown by comparing with many existing methods with 80.3% high accuracy. The training-validation loss and accuracy plots are presented to consider our good model fitting.

Suggested Citation

  • Cholamjiak, Watcharaporn & Suparatulatorn, Raweerote, 2023. "Strong convergence of a modified extragradient algorithm to solve pseudomonotone equilibrium and application to classification of diabetes mellitus," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    • Handle: RePEc:eee:chsofr:v:168:y:2023:i:c:s0960077923000097
    DOI: 10.1016/j.chaos.2023.113108
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    References listed on IDEAS

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    1. Rapeepan Kraikaew & Satit Saejung, 2014. "Strong Convergence of the Halpern Subgradient Extragradient Method for Solving Variational Inequalities in Hilbert Spaces," Journal of Optimization Theory and Applications, Springer, vol. 163(2), pages 399-412, November.
    2. Y. Censor & A. Gibali & S. Reich, 2011. "The Subgradient Extragradient Method for Solving Variational Inequalities in Hilbert Space," Journal of Optimization Theory and Applications, Springer, vol. 148(2), pages 318-335, February.
    3. Brahim-Belhouari, Sofiane & Bermak, Amine, 2004. "Gaussian process for nonstationary time series prediction," Computational Statistics & Data Analysis, Elsevier, vol. 47(4), pages 705-712, November.
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