BOXVIA: Bayesian optimization executable and visualizable application
Akimitsu Ishii,
Ryunosuke Kamijyo,
Akinori Yamanaka,
Akiyasu Yamamoto
Affiliations
Akimitsu Ishii
Department of Mechanical Systems Engineering, Graduate School of Engineering, Tokyo University of Agriculture and Technology, 2-24-16, Naka-cho, Koganei-shi, Tokyo 184-8588, Japan; Corresponding author.
Ryunosuke Kamijyo
Department of Mechanical Systems Engineering, Graduate School of Engineering, Tokyo University of Agriculture and Technology, 2-24-16, Naka-cho, Koganei-shi, Tokyo 184-8588, Japan
Akinori Yamanaka
Division of Advanced Mechanical Systems Engineering, Institute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16, Naka-cho, Koganei-shi, Tokyo 184-8588, Japan
Akiyasu Yamamoto
Division of Advanced Applied Physics, Institute of Engineering, Tokyo University of Agriculture and Technology, 2-24-16, Naka-cho, Koganei-shi, Tokyo 184-8588, Japan
Bayesian optimization (BO) has attracted attention in various research fields as a powerful probabilistic approach for solving optimization problems. To further facilitate the use of BO, we developed a graphical user interface-based Python application called BOXVIA. BOXVIA enables the use of BO without the construction of a computing environment and/or the need for programming skills. Moreover, BOXVIA helps users interpret the results of the BO process effectively through certain useful functionalities available for visualizing the mean function, standard deviation, and acquisition functions.
