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DESCRIPTION
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DESCRIPTION
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Package: mlr3tuning
Title: Hyperparameter Optimization for 'mlr3'
Version: 1.2.0.9000
Authors@R: c(
person("Marc", "Becker", , "marcbecker@posteo.de", role = c("cre", "aut"),
comment = c(ORCID = "0000-0002-8115-0400")),
person("Michel", "Lang", , "michellang@gmail.com", role = "aut",
comment = c(ORCID = "0000-0001-9754-0393")),
person("Jakob", "Richter", , "jakob1richter@gmail.com", role = "aut",
comment = c(ORCID = "0000-0003-4481-5554")),
person("Bernd", "Bischl", , "bernd_bischl@gmx.net", role = "aut",
comment = c(ORCID = "0000-0001-6002-6980")),
person("Daniel", "Schalk", , "daniel.schalk@stat.uni-muenchen.de", role = "aut",
comment = c(ORCID = "0000-0003-0950-1947"))
)
Description: Hyperparameter optimization package of the 'mlr3' ecosystem.
It features highly configurable search spaces via the 'paradox'
package and finds optimal hyperparameter configurations for any 'mlr3'
learner. 'mlr3tuning' works with several optimization algorithms e.g.
Random Search, Iterated Racing, Bayesian Optimization (in 'mlr3mbo')
and Hyperband (in 'mlr3hyperband'). Moreover, it can automatically
optimize learners and estimate the performance of optimized models
with nested resampling.
License: LGPL-3
URL: https://mlr3tuning.mlr-org.com, https://github.com/mlr-org/mlr3tuning
BugReports: https://github.com/mlr-org/mlr3tuning/issues
Depends:
mlr3 (>= 0.20.0),
paradox (>= 1.0.1),
R (>= 3.1.0)
Imports:
bbotk (>= 1.3.0),
checkmate (>= 2.0.0),
data.table,
lgr,
mlr3misc (>= 0.15.1),
R6
Suggests:
adagio,
future,
GenSA,
irace,
knitr,
mlflow,
mlr3learners (>= 0.7.0),
mlr3pipelines (>= 0.5.2),
nloptr,
rush,
rmarkdown,
rpart,
testthat (>= 3.0.0),
xgboost
VignetteBuilder:
knitr
Config/testthat/edition: 3
Config/testthat/parallel: false
Encoding: UTF-8
NeedsCompilation: no
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Collate:
'ArchiveAsyncTuning.R'
'ArchiveBatchTuning.R'
'AutoTuner.R'
'CallbackAsyncTuning.R'
'CallbackBatchTuning.R'
'ContextAsyncTuning.R'
'ContextBatchTuning.R'
'ObjectiveTuning.R'
'ObjectiveTuningAsync.R'
'ObjectiveTuningBatch.R'
'mlr_tuners.R'
'Tuner.R'
'TunerAsync.R'
'TunerAsyncDesignPoints.R'
'TunerAsyncFromOptimizerAsync.R'
'TunerAsyncGridSearch.R'
'TunerAsyncRandomSearch.R'
'TunerBatch.R'
'TunerBatchCmaes.R'
'TunerBatchDesignPoints.R'
'TunerBatchFromBatchOptimizer.R'
'TunerBatchGenSA.R'
'TunerBatchGridSearch.R'
'TunerBatchInternal.R'
'TunerBatchIrace.R'
'TunerBatchNLoptr.R'
'TunerBatchRandomSearch.R'
'TuningInstanceBatchSingleCrit.R'
'TuningInstanceAsyncMulticrit.R'
'TuningInstanceAsyncSingleCrit.R'
'TuningInstanceBatchMulticrit.R'
'TuningInstanceMultiCrit.R'
'TuningInstanceSingleCrit.R'
'as_search_space.R'
'as_tuner.R'
'assertions.R'
'auto_tuner.R'
'bibentries.R'
'extract_inner_tuning_archives.R'
'extract_inner_tuning_results.R'
'helper.R'
'mlr_callbacks.R'
'reexport.R'
'sugar.R'
'tune.R'
'tune_nested.R'
'zzz.R'