ParBayesianOptimization: Parallel Bayesian Optimization of Hyperparameters

Fast, flexible framework for implementing Bayesian optimization of model hyperparameters according to the methods described in Snoek et al. <doi:10.48550/arXiv.1206.2944>. The package allows the user to run scoring function in parallel, save intermediary results, and tweak other aspects of the process to fully utilize the computing resources available to the user.

Version: 1.2.6
Depends: R (≥ 3.4)
Imports: data.table (≥ 1.11.8), DiceKriging, stats, foreach, dbscan, lhs, crayon, ggplot2, ggpubr (≥ 0.2.4)
Suggests: knitr, rmarkdown, xgboost, doParallel, testthat
Published: 2022-10-18
DOI: 10.32614/CRAN.package.ParBayesianOptimization
Author: Samuel Wilson [aut, cre]
Maintainer: Samuel Wilson <samwilson303 at>
License: GPL-2
NeedsCompilation: no
Materials: README NEWS
CRAN checks: ParBayesianOptimization results


Reference manual: ParBayesianOptimization.pdf
Vignettes: Function Maximization
Sampling Multiple Parameter Sets at Once
Tuning Hyperparameters


Package source: ParBayesianOptimization_1.2.6.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): ParBayesianOptimization_1.2.6.tgz, r-oldrel (arm64): ParBayesianOptimization_1.2.6.tgz, r-release (x86_64): ParBayesianOptimization_1.2.6.tgz, r-oldrel (x86_64): ParBayesianOptimization_1.2.6.tgz
Old sources: ParBayesianOptimization archive

Reverse dependencies:

Reverse suggests: MachineShop, mlexperiments, mllrnrs, mlsurvlrnrs


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