BOXVIA: Bayesian optimization executable and visualizable application
Akimitsu Ishii, Ryunosuke Kamijyo, Akinori Yamanaka, Akiyasu Yamamoto
Abstract
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.
Topics & Concepts
Python (programming language)ExecutableComputer scienceBayesian optimizationGraphical user interfaceProbabilistic logicBayesian probabilityProgramming languageTheoretical computer scienceMachine learningArtificial intelligenceAdvanced Multi-Objective Optimization AlgorithmsAdvanced Bandit Algorithms ResearchGaussian Processes and Bayesian Inference