Distributions of the goodness-of-fit (GoF) values for all tested approaches and parameter spaces.

<p>The considered optimization methods and the respective dimensions of the parameter spaces are indicated on the horizontal axes (BO 2D, CMAES 2D, BO 3D and CMAES 3D in the low-dimensional cases and BO 103D, CMAES 103D, BO 99D and CMAES 99D in the high-dimensional ones) along with the detecte...

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Main Author: Kevin J. Wischnewski (21354521) (author)
Other Authors: Florian Jarre (2902498) (author), Simon B. Eickhoff (8355852) (author), Oleksandr V. Popovych (7866194) (author)
Published: 2025
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Summary:<p>The considered optimization methods and the respective dimensions of the parameter spaces are indicated on the horizontal axes (BO 2D, CMAES 2D, BO 3D and CMAES 3D in the low-dimensional cases and BO 103D, CMAES 103D, BO 99D and CMAES 99D in the high-dimensional ones) along with the detected GoF values on the vertical axes. Violins show the distributions of the median GoF values obtained for all subjects across 30 algorithm executions with random initial data (option 2, see Methods). The medians (across subjects) of the relative increase between the results obtained in different parameter spaces for a given algorithm are indicated in the plots together with -values of the Wilcoxon signed-rank test and the considered atlas: <b>(A)</b> the Schaefer atlas (Sch100) and <b>(B)</b> the Harvard-Oxford atlas (HO0Thr). Statistically significant differences are marked with an asterisk. The significance level of 5%, < 0.05, has been Bonferroni-corrected for multiple comparisons.</p>