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1 | 1 | Package: mlrMBO
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2 | 2 | Title: Bayesian Optimization and Model-Based Optimization of Expensive
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3 |
| - Black-Box Functions |
4 |
| -Version: 1.1.5.1 |
5 |
| -Description: Flexible and comprehensive R toolbox for model-based optimization |
6 |
| - ('MBO'), also known as Bayesian optimization. It implements the Efficient |
7 |
| - Global Optimization Algorithm and is designed for both single- and multi- |
8 |
| - objective optimization with mixed continuous, categorical and conditional |
9 |
| - parameters. The machine learning toolbox 'mlr' provide dozens of regression |
10 |
| - learners to model the performance of the target algorithm with respect to |
11 |
| - the parameter settings. It provides many different infill criteria to guide |
12 |
| - the search process. Additional features include multi-point batch proposal, |
13 |
| - parallel execution as well as visualization and sophisticated logging |
14 |
| - mechanisms, which is especially useful for teaching and understanding of |
15 |
| - algorithm behavior. 'mlrMBO' is implemented in a modular fashion, such that |
16 |
| - single components can be easily replaced or adapted by the user for specific |
17 |
| - use cases. |
18 |
| -Authors@R: c( |
19 |
| - person("Bernd", "Bischl", email = " [email protected]", role = c("aut"), comment = c(ORCID = "0000-0001-6002-6980")), |
20 |
| - person("Jakob", "Richter", email = " [email protected]", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-4481-5554")), |
21 |
| - person("Jakob", "Bossek", email = " [email protected]", role = "aut", comment = c(ORCID = "0000-0002-4121-4668")), |
22 |
| - person("Daniel", "Horn", email = " [email protected]", role = "aut"), |
23 |
| - person("Michel", "Lang", email = " [email protected]", role = "aut", comment = c(ORCID = "0000-0001-9754-0393")), |
24 |
| - person("Janek", "Thomas", email = " [email protected]", role = "aut", comment = c(ORCID = "0000-0003-4511-6245"))) |
| 3 | + Black-Box Functions |
| 4 | +Version: 1.1.5-9000 |
| 5 | +Authors@R: |
| 6 | + c(person(given = "Bernd", |
| 7 | + family = "Bischl", |
| 8 | + role = "aut", |
| 9 | + |
| 10 | + comment = c(ORCID = "0000-0001-6002-6980")), |
| 11 | + person(given = "Jakob", |
| 12 | + family = "Richter", |
| 13 | + role = c("aut", "cre"), |
| 14 | + |
| 15 | + comment = c(ORCID = "0000-0003-4481-5554")), |
| 16 | + person(given = "Jakob", |
| 17 | + family = "Bossek", |
| 18 | + role = "aut", |
| 19 | + |
| 20 | + comment = c(ORCID = "0000-0002-4121-4668")), |
| 21 | + person(given = "Daniel", |
| 22 | + family = "Horn", |
| 23 | + role = "aut", |
| 24 | + |
| 25 | + person(given = "Michel", |
| 26 | + family = "Lang", |
| 27 | + role = "aut", |
| 28 | + |
| 29 | + comment = c(ORCID = "0000-0001-9754-0393")), |
| 30 | + person(given = "Janek", |
| 31 | + family = "Thomas", |
| 32 | + role = "aut", |
| 33 | + |
| 34 | + comment = c(ORCID = "0000-0003-4511-6245"))) |
| 35 | +Description: Flexible and comprehensive R toolbox for model-based |
| 36 | + optimization ('MBO'), also known as Bayesian optimization. It |
| 37 | + implements the Efficient Global Optimization Algorithm and is designed |
| 38 | + for both single- and multi- objective optimization with mixed |
| 39 | + continuous, categorical and conditional parameters. The machine |
| 40 | + learning toolbox 'mlr' provide dozens of regression learners to model |
| 41 | + the performance of the target algorithm with respect to the parameter |
| 42 | + settings. It provides many different infill criteria to guide the |
| 43 | + search process. Additional features include multi-point batch |
| 44 | + proposal, parallel execution as well as visualization and |
| 45 | + sophisticated logging mechanisms, which is especially useful for |
| 46 | + teaching and understanding of algorithm behavior. 'mlrMBO' is |
| 47 | + implemented in a modular fashion, such that single components can be |
| 48 | + easily replaced or adapted by the user for specific use cases. |
25 | 49 | License: BSD_2_clause + file LICENSE
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26 | 50 | URL: https://github.com/mlr-org/mlrMBO
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27 | 51 | BugReports: https://github.com/mlr-org/mlrMBO/issues
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28 |
| -Depends: mlr (>= 2.10), ParamHelpers (>= 1.10), smoof (>= 1.5.1) |
29 |
| -Imports: backports (>= 1.1.0), BBmisc (>= 1.11), checkmate (>= 1.8.2), |
30 |
| - data.table, lhs, parallelMap (>= 1.3) |
31 |
| -Suggests: cmaesr (>= 1.0.3), ggplot2, DiceKriging, earth, emoa, GGally, |
32 |
| - gridExtra, kernlab, kknn, knitr, mco, nnet, party, |
33 |
| - randomForest, reshape2, rmarkdown, rgenoud, rpart, testthat, |
34 |
| - covr |
35 |
| -Encoding: UTF-8 |
| 52 | +Depends: |
| 53 | + mlr (>= 2.10), |
| 54 | + ParamHelpers (>= 1.10), |
| 55 | + smoof (>= 1.5.1) |
| 56 | +Imports: |
| 57 | + backports (>= 1.1.0), |
| 58 | + BBmisc (>= 1.11), |
| 59 | + checkmate (>= 1.8.2), |
| 60 | + data.table, |
| 61 | + lhs, |
| 62 | + parallelMap (>= 1.3) |
| 63 | +Suggests: |
| 64 | + cmaesr (>= 1.0.3), |
| 65 | + covr, |
| 66 | + DiceKriging, |
| 67 | + earth, |
| 68 | + emoa, |
| 69 | + GGally, |
| 70 | + ggplot2, |
| 71 | + gridExtra, |
| 72 | + kernlab, |
| 73 | + kknn, |
| 74 | + knitr, |
| 75 | + mco, |
| 76 | + nnet, |
| 77 | + party, |
| 78 | + randomForest, |
| 79 | + reshape2, |
| 80 | + rgenoud, |
| 81 | + rmarkdown, |
| 82 | + rpart, |
| 83 | + testthat |
| 84 | +VignetteBuilder: |
| 85 | + knitr |
36 | 86 | ByteCompile: yes
|
| 87 | +Encoding: UTF-8 |
37 | 88 | RoxygenNote: 7.1.1
|
38 |
| -VignetteBuilder: knitr |
39 |
| -NeedsCompilation: yes |
40 |
| -Packaged: 2022-07-04 07:35:16 UTC; ripley |
41 |
| -Author: Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), |
42 |
| - Jakob Richter [aut, cre] (<https://orcid.org/0000-0003-4481-5554>), |
43 |
| - Jakob Bossek [aut] (<https://orcid.org/0000-0002-4121-4668>), |
44 |
| - Daniel Horn [aut], |
45 |
| - Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), |
46 |
| - Janek Thomas [aut] (<https://orcid.org/0000-0003-4511-6245>) |
47 |
| -Maintainer: Jakob Richter < [email protected]> |
48 |
| -Repository: CRAN |
49 |
| -Date/Publication: 2022-07-04 08:50:50 UTC |
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