A set of tools for model-based optimization and tuning of algorithms (hyperparameter tuning). It includes surrogate models, optimizers, and design of experiment approaches. The main interface is spot, which uses sequentially updated surrogate models for the purpose of efficient optimization. The main goal is to ease the burden of objective function evaluations, when a single evaluation requires a significant amount of resources.
|Author||Thomas Bartz-Beielstein [aut, cre] (<https://orcid.org/0000-0002-5938-5158>), Martin Zaefferer [aut] (<https://orcid.org/0000-0003-2372-2092>), Frederik Rehbach [aut] (<https://orcid.org/0000-0003-0922-8629>), Margarita Rebolledo [ctb], Joerg Stork [ctb] (0000-0002-7471-3498), Christian Lasarczyk [ctb]|
|Maintainer||Thomas Bartz-Beielstein <firstname.lastname@example.org>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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