bbotk, blockCV (>= 2.1.1), caret, CAST, ggsci, ggtext, knitr,
lgr, mlr3filters, mlr3pipelines, mlr3tuning, patchwork, plotly,
raster, rgdal, rmarkdown, rpart, sf, skmeans, sperrorest,
testthat (>= 3.0.0), vdiffr (>= 1.0.0), withr

checkmate, data.table, ggplot2, mlr3 (>= 0.12.0), mlr3misc (>=
0.9.2), paradox, R6, utils
bbotk, blockCV (>= 2.1.4), caret, CAST, ggsci, ggtext, knitr,
lgr, mlr3filters, mlr3pipelines, mlr3tuning, patchwork, plotly,
raster, rgdal, rmarkdown, rpart, sf, skmeans, sperrorest,
testthat (>= 3.0.0), vdiffr (>= 1.0.0), withr

c(
person("Patrick", "Schratz", , "patrick.schratz@gmail.com", role = c("aut", "cre"),
comment = c(ORCID = "0000-0003-0748-6624")),
person("Marc", "Becker", , "marcbecker@posteo.de", role = "aut",
comment = c(ORCID = "0000-0002-8115-0400")),
person("Jannes", "Muenchow", , "jannes.muenchow@uni-jena.de", role = "ctb",
comment = c(ORCID = "0000-0001-7834-4717")),
person("Michel", "Lang", , "michellang@gmail.com", role = "ctb",
comment = c(ORCID = "0000-0001-9754-0393"))
)
checkmate, data.table, ggplot2, mlr3misc (>= 0.9.2), paradox,
R6, utils
bbotk, blockCV (>= 2.1.4), caret, ggsci, ggtext, knitr, lgr,
mlr3filters, mlr3pipelines, mlr3tuning, patchwork, here,
plotly, raster, rgdal, rmarkdown, rpart, sf, skmeans,
sperrorest, terra, testthat (>= 3.0.0), vdiffr (>= 1.0.0),
withr

checkmate, data.table, ggplot2 (>= 3.4.0), mlr3misc (>=
0.11.0), paradox, R6, utils

c(person(given = "Michel",
family = "Lang",
role = c("cre", "aut"),
email = "michellang@gmail.com",
comment = c(ORCID = "0000-0001-9754-0393")),
person(given = "Jakob",
family = "Richter",
role = "aut",
email = "jakob1richter@gmail.com",
comment = c(ORCID = "0000-0003-4481-5554")),
person(given = "Bernd",
family = "Bischl",
role = "aut",
email = "bernd_bischl@gmx.net",
comment = c(ORCID = "0000-0001-6002-6980")),
person(given = "Daniel",
family = "Schalk",
role = "aut",
email = "daniel.schalk@stat.uni-muenchen.de",
comment = c(ORCID = "0000-0003-0950-1947")))
Implements methods for hyperparameter tuning with
'mlr3', e.g. Grid Search, Random Search, or Simulated Annealing.
Various termination criteria can be set and combined.  The class
'AutoTuner' provides a convenient way to perform nested resampling in
combination with 'mlr3'.
checkmate (>= 1.9.4), data.table, lgr, mlr3, mlr3misc,
paradox, R6
'AutoTuner.R' 'mlr_terminators.R' 'Terminator.R'
'TerminatorClockTime.R' 'TerminatorCombo.R' 'TerminatorEvals.R'
'TerminatorModelTime.R' 'TerminatorNone.R'
'TerminatorPerfReached.R' 'TerminatorStagnation.R'
'mlr_tuners.R' 'Tuner.R' 'TunerDesignPoints.R' 'TunerGenSA.R'
'TunerGridSearch.R' 'TunerRandomSearch.R' 'TuningInstance.R'
'assertions.R' 'helper.R' 'sugar.R' 'zzz.R'