Flexible automated machine learning (AutoML) system for the
'mlr3' ecosystem. Automatically selects a suitable machine learning
algorithm and tunes its hyperparameters for a given task. Constructs
preprocessing pipelines with multiple parallel branches using
'mlr3pipelines' and jointly optimizes them together with the learners
using 'mlr3tuning'. The optimization is driven by asynchronous
decentralized Bayesian optimization by Egele et al. (2023)
<doi:10.1109/e-Science58273.2023.10254839>.
| Version: |
0.1.0 |
| Depends: |
mlr3 (≥ 1.6.0), mlr3tuning (≥ 1.6.0), R (≥ 3.3.0), rush (≥
1.2.1) |
| Imports: |
bbotk (≥ 1.7.1), checkmate, data.table, lhs, mlr3learners (≥
0.14.0), mlr3mbo (≥ 1.2.0), mlr3misc (≥ 0.15.1), mlr3pipelines, paradox (≥ 1.0.1), R6, utils |
| Suggests: |
callr, e1071, fastai, glmnet, kknn, lgr, lightgbm, MASS, mirai, mlr3extralearners, mlr3torch (≥ 0.3.3), mlr3viz, ranger, redux, reticulate, rpart, testthat (≥ 3.0.0), torch, xgboost (≥ 3.2.1.1) |
| Published: |
2026-09-03 |
| DOI: |
10.32614/CRAN.package.mlr3automl |
| Author: |
Marc Becker  [cre,
aut, cph],
Damir Pulatov [aut],
Baisu Zhou [aut],
Lona Koers [aut] |
| Maintainer: |
Marc Becker <marcbecker at posteo.de> |
| BugReports: |
https://github.com/mlr-org/mlr3automl/issues |
| License: |
LGPL-3 |
| URL: |
https://mlr3automl.mlr-org.com,
https://github.com/mlr-org/mlr3automl |
| NeedsCompilation: |
no |
| Additional_repositories: |
https://mlr-org.r-universe.dev |
| Materials: |
README, NEWS |
| CRAN checks: |
mlr3automl results |