Package: mlr3 Title: Machine Learning in R - Next Generation Version: 1.8.0 Authors@R: c( person("Michel", "Lang", , "michellang@gmail.com", role = "aut", comment = c(ORCID = "0000-0001-9754-0393")), person("Bernd", "Bischl", , "bernd_bischl@gmx.net", role = "aut", comment = c(ORCID = "0000-0001-6002-6980")), person("Jakob", "Richter", , "jakob1richter@gmail.com", role = "aut", comment = c(ORCID = "0000-0003-4481-5554")), person("Patrick", "Schratz", , "patrick.schratz@gmail.com", role = "aut", comment = c(ORCID = "0000-0003-0748-6624")), person("Giuseppe", "Casalicchio", , "giuseppe.casalicchio@stat.uni-muenchen.de", role = "ctb", comment = c(ORCID = "0000-0001-5324-5966")), person("Stefan", "Coors", , "mail@stefancoors.de", role = "ctb", comment = c(ORCID = "0000-0002-7465-2146")), person("Quay", "Au", , "quayau@gmail.com", role = "ctb", comment = c(ORCID = "0000-0002-5252-8902")), person("Martin", "Binder", , "mlr.developer@mb706.com", role = "aut"), person("Florian", "Pfisterer", , "pfistererf@googlemail.com", role = "aut", comment = c(ORCID = "0000-0001-8867-762X")), person("Raphael", "Sonabend", , "raphaelsonabend@gmail.com", role = "aut", comment = c(ORCID = "0000-0001-9225-4654")), person("Lennart", "Schneider", , "lennart.sch@web.de", role = "ctb", comment = c(ORCID = "0000-0003-4152-5308")), person("Marc", "Becker", , "marcbecker@posteo.de", role = c("cre", "aut"), comment = c(ORCID = "0000-0002-8115-0400")), person("Sebastian", "Fischer", , "sebf.fischer@gmail.com", role = "aut", comment = c(ORCID = "0000-0002-9609-3197")), person("Lona", "Koers", , "lona.koers@gmail.com", role = "ctb"), person("John", "Zobolas", , "bblodfon@gmail.com", role = "ctb", comment = c(ORCID = "0000-0002-3609-8674")), person("Maximilian", "Mücke", , "muecke.maximilian@gmail.com", role = "ctb", comment = c(ORCID = "0009-0000-9432-9795")), person("Keno", "Mersmann", , "keno.mersmann@gmail.com", role = "ctb") ) Description: Efficient, object-oriented programming on the building blocks of machine learning. Provides 'R6' objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While 'mlr3' focuses on the core computational operations, add-on packages provide additional functionality. License: LGPL-3 URL: https://mlr3.mlr-org.com, https://github.com/mlr-org/mlr3 BugReports: https://github.com/mlr-org/mlr3/issues Depends: R (>= 3.5.0) Imports: R6 (>= 2.4.1), backports (>= 1.5.0), checkmate (>= 2.0.0), cli, data.table (>= 1.15.0), evaluate (>= 1.0.4), future, future.apply (>= 1.5.0), lgr (>= 0.3.4), mirai (>= 2.4.1), methods, mlbench (>= 2.1-11), mlr3measures (>= 1.2.0), mlr3misc (>= 0.21.0), parallelly, palmerpenguins, paradox (>= 1.0.1), uuid Suggests: callr, codetools, datasets, future.callr, mlr3data, progressr, remotes, RhpcBLASctl, rpart, testthat (>= 3.3.0) Encoding: UTF-8 Config/testthat/edition: 3 Config/testthat/parallel: false NeedsCompilation: no Roxygen: list(markdown = TRUE, r6 = TRUE) Collate: 'mlr_reflections.R' 'BenchmarkResult.R' 'CallbackResample.R' 'ContextResample.R' 'warn_deprecated.R' 'DataBackend.R' 'DataBackendCbind.R' 'DataBackendDataTable.R' 'DataBackendRbind.R' 'DataBackendRename.R' 'HotstartStack.R' 'Learner.R' 'LearnerClassif.R' 'mlr_learners.R' 'LearnerClassifDebug.R' 'LearnerClassifFeatureless.R' 'LearnerClassifRpart.R' 'LearnerRegr.R' 'LearnerRegrDebug.R' 'LearnerRegrFeatureless.R' 'LearnerRegrRpart.R' 'Measure.R' 'mlr_measures.R' 'MeasureAIC.R' 'MeasureBIC.R' 'MeasureValidScore.R' 'MeasureBestValidScore.R' 'MeasureClassif.R' 'MeasureClassifCosts.R' 'MeasureDebug.R' 'MeasureElapsedTime.R' 'MeasureInternalValidScore.R' 'MeasureOOBError.R' 'MeasureRegr.R' 'MeasureRegrPinball.R' 'MeasureRegrRQR.R' 'MeasureRegrRSQ.R' 'MeasureSelectedFeatures.R' 'MeasureSimilarity.R' 'MeasureSimple.R' 'Prediction.R' 'PredictionClassif.R' 'PredictionData.R' 'PredictionDataClassif.R' 'PredictionDataRegr.R' 'PredictionRegr.R' 'ResampleResult.R' 'Resampling.R' 'mlr_resamplings.R' 'ResamplingBootstrap.R' 'ResamplingCV.R' 'ResamplingCustom.R' 'ResamplingCustomCV.R' 'ResamplingHoldout.R' 'ResamplingInsample.R' 'ResamplingLOO.R' 'ResamplingRepeatedCV.R' 'ResamplingSubsampling.R' 'ResultData.R' 'Task.R' 'TaskSupervised.R' 'TaskClassif.R' 'mlr_tasks.R' 'TaskClassif_breast_cancer.R' 'TaskClassif_diabetes.R' 'TaskClassif_german_credit.R' 'TaskClassif_iris.R' 'TaskClassif_penguins.R' 'TaskClassif_sonar.R' 'TaskClassif_spam.R' 'TaskClassif_wine.R' 'TaskClassif_zoo.R' 'TaskGenerator.R' 'mlr_task_generators.R' 'TaskGenerator2DNormals.R' 'TaskGeneratorCassini.R' 'TaskGeneratorCircle.R' 'TaskGeneratorFriedman1.R' 'TaskGeneratorMoons.R' 'TaskGeneratorPeak.R' 'TaskGeneratorSimplex.R' 'TaskGeneratorSmiley.R' 'TaskGeneratorSpirals.R' 'TaskGeneratorXor.R' 'TaskRegr.R' 'TaskRegr_california_housing.R' 'TaskRegr_mtcars.R' 'TaskUnsupervised.R' 'as_benchmark_result.R' 'as_data_backend.R' 'as_learner.R' 'as_measure.R' 'as_prediction.R' 'as_prediction_classif.R' 'as_prediction_data.R' 'as_prediction_regr.R' 'as_resample_result.R' 'as_resampling.R' 'as_result_data.R' 'as_task.R' 'as_task_classif.R' 'as_task_regr.R' 'as_task_unsupervised.R' 'assertions.R' 'auto_convert.R' 'benchmark.R' 'benchmark_grid.R' 'bibentries.R' 'default_fallback.R' 'default_measures.R' 'fix_factor_levels.R' 'helper.R' 'helper_data_table.R' 'helper_exec.R' 'helper_hashes.R' 'install_pkgs.R' 'marshal.R' 'mlr_callbacks.R' 'mlr_sugar.R' 'mlr_test_helpers.R' 'partition.R' 'predict.R' 'reexports.R' 'resample.R' 'score_roc_measures.R' 'set_threads.R' 'set_validate.R' 'task_converters.R' 'worker.R' 'zzz.R' Config/roxygen2/version: 8.1.0 Repository: https://mlr-org.r-universe.dev Date/Publication: 2026-08-21 07:25:38 UTC RemoteUrl: https://github.com/mlr-org/mlr3 RemoteRef: v1.8.0 RemoteSha: 319c9057c4d2070edc5a9e0dca8f79926a7c410c Packaged: 2026-09-20 09:44:23 UTC; root Author: Michel Lang [aut] (ORCID: ), Bernd Bischl [aut] (ORCID: ), Jakob Richter [aut] (ORCID: ), Patrick Schratz [aut] (ORCID: ), Giuseppe Casalicchio [ctb] (ORCID: ), Stefan Coors [ctb] (ORCID: ), Quay Au [ctb] (ORCID: ), Martin Binder [aut], Florian Pfisterer [aut] (ORCID: ), Raphael Sonabend [aut] (ORCID: ), Lennart Schneider [ctb] (ORCID: ), Marc Becker [cre, aut] (ORCID: ), Sebastian Fischer [aut] (ORCID: ), Lona Koers [ctb], John Zobolas [ctb] (ORCID: ), Maximilian Mücke [ctb] (ORCID: ), Keno Mersmann [ctb] Maintainer: Marc Becker