SPOT: Sequential Parameter Optimization Toolbox

A set of tools for model-based optimization and tuning of algorithms (hyperparameter tuning respectively hyperparameter optimization). 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.

Version: 2.11.14
Depends: R (≥ 3.5.0)
Imports: DEoptim, ggplot2, glmnet, graphics, grDevices, laGP, MASS, nloptr, plgp, plotly, rpart, randomForest, ranger, rgenoud, rsm, stats, utils
Suggests: batchtools, car, farff, knitr, microbenchmark, rmarkdown, OpenML, party, RColorBrewer, readr, testthat
Published: 2022-06-25
Author: Thomas Bartz-Beielstein ORCID iD [aut, cre], Martin Zaefferer ORCID iD [aut], Frederik Rehbach ORCID iD [aut], Margarita Rebolledo [ctb], Joerg Stork [ctb] (0000-0002-7471-3498), Christian Lasarczyk [ctb]
Maintainer: Thomas Bartz-Beielstein <tbb at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: SPOT citation info
Materials: NEWS
In views: Optimization
CRAN checks: SPOT results


Reference manual: SPOT.pdf
Vignettes: SPOTVignetteNutshell


Package source: SPOT_2.11.14.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): SPOT_2.11.14.tgz, r-oldrel (arm64): SPOT_2.11.14.tgz, r-release (x86_64): SPOT_2.11.14.tgz
Old sources: SPOT archive

Reverse dependencies:

Reverse imports:, SPOTMisc


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