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ParamHelpers: Helpers for Parameters in Black-Box Optimization, Tuning and Machine Learning

Functions for parameter descriptions and operations in black-box optimization, tuning and machine learning. Parameters can be described (type, constraints, defaults, etc.), combined to parameter sets and can in general be programmed on. A useful OptPath object (archive) to log function evaluations is also provided.

Version: 1.14.1
Imports: backports, BBmisc (≥ 1.10), checkmate (≥ 1.8.2), fastmatch, methods
Suggests: interp, covr, eaf, emoa, GGally, ggplot2, grid, gridExtra, irace (≥ 2.1), lhs, plyr, reshape2, testthat
Published: 2022-07-04
DOI: 10.32614/CRAN.package.ParamHelpers
Author: Bernd Bischl ORCID iD [aut], Michel Lang ORCID iD [aut], Jakob Richter ORCID iD [cre, aut], Jakob Bossek [aut], Daniel Horn [aut], Karin Schork [ctb], Pascal Kerschke [aut]
Maintainer: Jakob Richter <code at jakob-r.de>
BugReports: https://github.com/mlr-org/ParamHelpers/issues
License: BSD_2_clause + file LICENSE
URL: https://paramhelpers.mlr-org.com, https://github.com/mlr-org/ParamHelpers
NeedsCompilation: yes
Materials: NEWS
CRAN checks: ParamHelpers results

Documentation:

Reference manual: ParamHelpers.pdf

Downloads:

Package source: ParamHelpers_1.14.1.tar.gz
Windows binaries: r-devel: ParamHelpers_1.14.1.zip, r-release: ParamHelpers_1.14.1.zip, r-oldrel: ParamHelpers_1.14.1.zip
macOS binaries: r-release (arm64): ParamHelpers_1.14.1.tgz, r-oldrel (arm64): ParamHelpers_1.14.1.tgz, r-release (x86_64): ParamHelpers_1.14.1.tgz, r-oldrel (x86_64): ParamHelpers_1.14.1.tgz
Old sources: ParamHelpers archive

Reverse dependencies:

Reverse depends: cmaesr, ecr, mlr, mlrCPO, mlrMBO, smoof
Reverse imports: aslib, CEGO, EFAfactors, glmnetr, roseRF, tramnet, tuneRanger, varycoef
Reverse suggests: bnclassify, ChemoSpec2D, dynparam, flacco, irace, llama, mlrintermbo, OmnipathR, OpenML

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ParamHelpers to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.