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DESCRIPTION

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Package: mlrMBO
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Title: Bayesian Optimization and Model-Based Optimization of Expensive
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Black-Box Functions
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Version: 1.1.5.1
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Description: Flexible and comprehensive R toolbox for model-based optimization
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('MBO'), also known as Bayesian optimization. It implements the Efficient
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Global Optimization Algorithm and is designed for both single- and multi-
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objective optimization with mixed continuous, categorical and conditional
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parameters. The machine learning toolbox 'mlr' provide dozens of regression
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learners to model the performance of the target algorithm with respect to
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the parameter settings. It provides many different infill criteria to guide
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the search process. Additional features include multi-point batch proposal,
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parallel execution as well as visualization and sophisticated logging
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mechanisms, which is especially useful for teaching and understanding of
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algorithm behavior. 'mlrMBO' is implemented in a modular fashion, such that
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single components can be easily replaced or adapted by the user for specific
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use cases.
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Authors@R: c(
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person("Bernd", "Bischl", email = "[email protected]", role = c("aut"), comment = c(ORCID = "0000-0001-6002-6980")),
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person("Jakob", "Richter", email = "[email protected]", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-4481-5554")),
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person("Jakob", "Bossek", email = "[email protected]", role = "aut", comment = c(ORCID = "0000-0002-4121-4668")),
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person("Daniel", "Horn", email = "[email protected]", role = "aut"),
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person("Michel", "Lang", email = "[email protected]", role = "aut", comment = c(ORCID = "0000-0001-9754-0393")),
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person("Janek", "Thomas", email = "[email protected]", role = "aut", comment = c(ORCID = "0000-0003-4511-6245")))
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Black-Box Functions
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Version: 1.1.5-9000
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Authors@R:
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c(person(given = "Bernd",
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family = "Bischl",
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role = "aut",
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email = "[email protected]",
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comment = c(ORCID = "0000-0001-6002-6980")),
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person(given = "Jakob",
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family = "Richter",
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role = c("aut", "cre"),
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email = "[email protected]",
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comment = c(ORCID = "0000-0003-4481-5554")),
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person(given = "Jakob",
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family = "Bossek",
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role = "aut",
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email = "[email protected]",
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comment = c(ORCID = "0000-0002-4121-4668")),
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person(given = "Daniel",
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family = "Horn",
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role = "aut",
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email = "[email protected]"),
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person(given = "Michel",
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family = "Lang",
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role = "aut",
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email = "[email protected]",
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comment = c(ORCID = "0000-0001-9754-0393")),
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person(given = "Janek",
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family = "Thomas",
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role = "aut",
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email = "[email protected]",
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comment = c(ORCID = "0000-0003-4511-6245")))
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Description: Flexible and comprehensive R toolbox for model-based
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optimization ('MBO'), also known as Bayesian optimization. It
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implements the Efficient Global Optimization Algorithm and is designed
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for both single- and multi- objective optimization with mixed
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continuous, categorical and conditional parameters. The machine
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learning toolbox 'mlr' provide dozens of regression learners to model
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the performance of the target algorithm with respect to the parameter
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settings. It provides many different infill criteria to guide the
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search process. Additional features include multi-point batch
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proposal, parallel execution as well as visualization and
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sophisticated logging mechanisms, which is especially useful for
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teaching and understanding of algorithm behavior. 'mlrMBO' is
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implemented in a modular fashion, such that single components can be
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easily replaced or adapted by the user for specific use cases.
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License: BSD_2_clause + file LICENSE
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URL: https://github.com/mlr-org/mlrMBO
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BugReports: https://github.com/mlr-org/mlrMBO/issues
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Depends: mlr (>= 2.10), ParamHelpers (>= 1.10), smoof (>= 1.5.1)
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Imports: backports (>= 1.1.0), BBmisc (>= 1.11), checkmate (>= 1.8.2),
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data.table, lhs, parallelMap (>= 1.3)
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Suggests: cmaesr (>= 1.0.3), ggplot2, DiceKriging, earth, emoa, GGally,
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gridExtra, kernlab, kknn, knitr, mco, nnet, party,
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randomForest, reshape2, rmarkdown, rgenoud, rpart, testthat,
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covr
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Encoding: UTF-8
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Depends:
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mlr (>= 2.10),
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ParamHelpers (>= 1.10),
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smoof (>= 1.5.1)
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Imports:
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backports (>= 1.1.0),
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BBmisc (>= 1.11),
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checkmate (>= 1.8.2),
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data.table,
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lhs,
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parallelMap (>= 1.3)
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Suggests:
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cmaesr (>= 1.0.3),
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covr,
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DiceKriging,
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earth,
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emoa,
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GGally,
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ggplot2,
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gridExtra,
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kernlab,
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kknn,
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knitr,
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mco,
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nnet,
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party,
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randomForest,
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reshape2,
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rgenoud,
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rmarkdown,
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rpart,
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testthat
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VignetteBuilder:
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knitr
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ByteCompile: yes
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Encoding: UTF-8
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RoxygenNote: 7.1.1
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VignetteBuilder: knitr
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NeedsCompilation: yes
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Packaged: 2022-07-04 07:35:16 UTC; ripley
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Author: Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>),
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Jakob Richter [aut, cre] (<https://orcid.org/0000-0003-4481-5554>),
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Jakob Bossek [aut] (<https://orcid.org/0000-0002-4121-4668>),
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Daniel Horn [aut],
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Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>),
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Janek Thomas [aut] (<https://orcid.org/0000-0003-4511-6245>)
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Maintainer: Jakob Richter <[email protected]>
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Repository: CRAN
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Date/Publication: 2022-07-04 08:50:50 UTC

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