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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 (may not be active yet) |
| Author: | Marc Becker |
| 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 |
| Reference manual: | mlr3automl.html , mlr3automl.pdf |
| Package source: | mlr3automl_0.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: mlr3automl_0.1.0.zip, r-oldrel: not available |
| macOS binaries: | r-release (arm64): mlr3automl_0.1.0.tgz, r-oldrel (arm64): mlr3automl_0.1.0.tgz, r-release (x86_64): mlr3automl_0.1.0.tgz, r-oldrel (x86_64): mlr3automl_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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