ParamHelpers: Helpers for Parameters in Black-Box Optimization, Tuning and Machine Learning (original) (raw)
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: | 1.14.2 |
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Imports: | backports, BBmisc (≥ 1.10), checkmate (≥ 1.8.2), fastmatch, methods |
Suggests: | akima, covr, eaf, emoa, GGally, ggplot2, grid, gridExtra, irace (≥ 2.1), lhs, plyr, reshape2, testthat |
Published: | 2025-01-09 |
DOI: | 10.32614/CRAN.package.ParamHelpers |
Author: | Bernd Bischl |
Maintainer: | Martin Binder <mlr.developer at mb706.com> |
BugReports: | https://github.com/mlr-org/ParamHelpers/issues |
License: | BSD_2_clause + file |
URL: | https://paramhelpers.mlr-org.com,https://github.com/mlr-org/ParamHelpers |
NeedsCompilation: | yes |
Materials: | NEWS |
CRAN checks: | ParamHelpers results |
Documentation:
Downloads:
Reverse dependencies:
Reverse depends: | cmaesr, ecr, mlr, mlrCPO, mlrMBO, smoof |
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Reverse imports: | aslib, FactorHet, glmnetr, Polytect, roseRF, tramnet, tuneRanger, varycoef |
Reverse suggests: | binaryRL, bnclassify, ChemoSpec2D, dynparam, flacco, llama, mlrintermbo, OmnipathR, OpenML |
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