mlrintermbo: Model-Based Optimization for 'mlr3' Through 'mlrMBO'

The 'mlrMBO' package can ordinarily not be used for optimization within 'mlr3', because of incompatibilities of their respective class systems. 'mlrintermbo' offers a compatibility interface that provides 'mlrMBO' as an 'mlr3tuning' 'Tuner' object, for tuning of machine learning algorithms within 'mlr3', as well as a 'bbotk' 'Optimizer' object for optimization of general objective functions using the 'bbotk' black box optimization framework. The control parameters of 'mlrMBO' are faithfully reproduced as a 'paradox' 'ParamSet'.

Version: 0.5.0
Imports: backports, checkmate, data.table, mlr3misc (≥ 0.1.4), paradox, R6, lhs, callr, bbotk, mlr3tuning
Suggests: mlr, ParamHelpers, testthat, rgenoud, DiceKriging, emoa, cmaesr, randomForest, smoof, lgr, mlr3, mlr3learners, mlr3pipelines, mlrMBO, ranger, rpart
Published: 2021-03-01
Author: Martin Binder [aut, cre]
Maintainer: Martin Binder <developer.mb706 at doublecaret.com>
BugReports: https://github.com/mb706/mlrintermbo/issues
License: LGPL-3
URL: https://github.com/mb706/mlrintermbo
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mlrintermbo results

Downloads:

Reference manual: mlrintermbo.pdf
Package source: mlrintermbo_0.5.0.tar.gz
Windows binaries: r-devel: mlrintermbo_0.5.0.zip, r-release: mlrintermbo_0.5.0.zip, r-oldrel: mlrintermbo_0.5.0.zip
macOS binaries: r-release: mlrintermbo_0.5.0.tgz, r-oldrel: mlrintermbo_0.5.0.tgz

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