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 gmail.com>
BugReports:	https://github.com/AnotherSamWilson/ParBayesianOptimization/issues
License:	GPL-2
URL:	https://github.com/AnotherSamWilson/ParBayesianOptimization
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	ParBayesianOptimization results

Documentation:

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

Downloads:

Package source:	ParBayesianOptimization_1.2.6.tar.gz
Windows binaries:	r-devel: ParBayesianOptimization_1.2.6.zip, r-release: ParBayesianOptimization_1.2.6.zip, r-oldrel: ParBayesianOptimization_1.2.6.zip
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

Linking:

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