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All Journal International Journal of Computing Science and Applied Mathematics-IJCSAM
Mustika Hadijati
University of Mataram
Mathematics

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Metaheuristic Search in Mixed Kernel and Spline Truncated Non-parametric Regression Mustika Hadijati; Irwansyah Irwansyah; Nurul Fitriyani; Muhammad Sopian Sauri
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 11 No. 2 (2025)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.ijcsam.v11i2.8841

Abstract

Non-parametric regressions are widely used in data analysis because of their flexibility. Apart from their applicability, it is not easy to find the optimal parameters of the corresponding non-parametric models. This situation is caused by the nonexistence of a closed formula of the optimal parameters. In this paper, we propose a metaheuristic approach for optimal parameter search in mixed kernel and truncated spline and kernel regression. Moreover, we provide examples on how to implement the proposed algorithm to both real and simulated datasets. The results indicate that the algorithm yields highly accurate predictions for mixed truncated spline and kernel regression models.
Co-Authors Irwansyah Irwansyah Muhammad Sopian Sauri Nurul Fitriyani