Automated Machine Learning for 'mlr3' R package mlr3automl version 0.1.0 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>. Software 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) Marc Becker <marcbecker@posteo.de> Comprehensive R Archive Network (CRAN) Marc Becker [cre, aut, cph] (ORCID: <https://orcid.org/0000-0002-8115-0400>), Damir Pulatov [aut], Baisu Zhou [aut], Lona Koers [aut] LGPL-3 2026-09-03 application/tgz https://CRAN.R-project.org/package=mlr3automl doi:10.32614/CRAN.package.mlr3automl