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DESCRIPTION
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DESCRIPTION
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Package: mlr3
Title: Machine Learning in R - Next Generation
Version: 0.19.0.9000
Authors@R:
c(
person("Michel", "Lang", , "michellang@gmail.com", role = c("cre", "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 = "aut",
comment = c(ORCID = "0000-0002-8115-0400")),
person("Sebastian", "Fischer", , "sebf.fischer@gmail.com", role = "ctb",
comment = c(ORCID = "0000-0002-9609-3197"))
)
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 (>= 3.1.0)
Imports:
R6 (>= 2.4.1),
backports,
checkmate (>= 2.0.0),
data.table (>= 1.15.0),
evaluate,
future,
future.apply (>= 1.5.0),
lgr (>= 0.3.4),
mlbench,
mlr3measures (>= 0.4.1),
mlr3misc (>= 0.15.0),
parallelly,
palmerpenguins,
paradox (>= 0.10.0),
RhpcBLASctl,
uuid
Suggests:
Matrix,
callr,
codetools,
datasets,
future.callr,
mlr3data,
progressr,
remotes,
rpart,
testthat (>= 3.1.0)
Encoding: UTF-8
Config/testthat/edition: 3
Config/testthat/parallel: false
NeedsCompilation: no
Roxygen: list(markdown = TRUE, r6 = TRUE)
RoxygenNote: 7.3.1
Collate:
'mlr_reflections.R'
'BenchmarkResult.R'
'DataBackend.R'
'DataBackendCbind.R'
'DataBackendDataTable.R'
'DataBackendMatrix.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'
'MeasureClassif.R'
'MeasureClassifCosts.R'
'MeasureDebug.R'
'MeasureElapsedTime.R'
'MeasureOOBError.R'
'MeasureRegr.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_german_credit.R'
'TaskClassif_iris.R'
'TaskClassif_penguins.R'
'TaskClassif_pima.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'
'TaskGeneratorSimplex.R'
'TaskGeneratorSmiley.R'
'TaskGeneratorSpirals.R'
'TaskGeneratorXor.R'
'TaskRegr.R'
'TaskRegr_boston_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_measures.R'
'fix_factor_levels.R'
'helper.R'
'helper_data_table.R'
'helper_exec.R'
'helper_hashes.R'
'helper_print.R'
'install_pkgs.R'
'marshal.R'
'mlr_sugar.R'
'mlr_test_helpers.R'
'partition.R'
'predict.R'
'reexports.R'
'resample.R'
'set_threads.R'
'task_converters.R'
'worker.R'
'zzz.R'