Package: mlr3
Title: Machine Learning in R - Next Generation
Version: 0.1.1
Authors@R: 
    c(person(given = "Michel",
             family = "Lang",
             role = c("cre", "aut"),
             email = "michellang@gmail.com",
             comment = c(ORCID = "0000-0001-9754-0393")),
      person(given = "Bernd",
             family = "Bischl",
             role = "aut",
             email = "bernd_bischl@gmx.net",
             comment = c(ORCID = "0000-0001-6002-6980")),
      person(given = "Jakob",
             family = "Richter",
             role = "aut",
             email = "jakob1richter@gmail.com",
             comment = c(ORCID = "0000-0003-4481-5554")),
      person(given = "Patrick",
             family = "Schratz",
             role = "aut",
             email = "patrick.schratz@gmail.com",
             comment = c(ORCID = "0000-0003-0748-6624")),
      person(given = "Giuseppe",
             family = "Casalicchio",
             role = "ctb",
             email = "giuseppe.casalicchio@stat.uni-muenchen.de",
             comment = c(ORCID = "0000-0001-5324-5966")),
      person(given = "Stefan",
             family = "Coors",
             role = "ctb",
             email = "mail@stefancoors.de",
             comment = c(ORCID = "0000-0002-7465-2146")),
      person(given = "Quay",
             family = "Au",
             role = "ctb",
             email = "quayau@gmail.com",
             comment = c(ORCID = "0000-0002-5252-8902")),
      person(given = "Martin",
             family = "Binder",
             role = "aut",
             email = "mlr.developer@mb706.com"))
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://github.com/mlr-org/mlr3
BugReports: https://github.com/mlr-org/mlr3/issues
Depends: R (>= 3.1.0)
Imports: backports, checkmate (>= 1.9.3), data.table, digest, lgr (>=
        0.3.0), Metrics, mlbench, mlr3misc (>= 0.1.1), paradox, R6
Suggests: callr, datasets, devtools, evaluate, future (>= 1.9.0),
        future.apply (>= 1.1.0), future.callr, Matrix, rpart, testthat,
        titanic
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
RoxygenNote: 6.1.1
Collate: 'mlr_reflections.R' 'BenchmarkResult.R' 'DataBackend.R'
        'DataBackendCbind.R' 'DataBackendDataTable.R'
        'DataBackendMatrix.R' 'DataBackendRbind.R' 'Generator.R'
        'mlr_generators.R' 'Generator2DNormals.R'
        'GeneratorFriedman1.R' 'GeneratorSmiley.R' 'GeneratorXor.R'
        'Learner.R' 'LearnerClassif.R' 'mlr_learners.R'
        'LearnerClassifDebug.R' 'LearnerClassifFeatureless.R'
        'LearnerClassifRpart.R' 'LearnerRegr.R'
        'LearnerRegrFeatureless.R' 'LearnerRegrRpart.R' 'Measure.R'
        'MeasureClassif.R' 'mlr_measures.R' 'MeasureClassifACC.R'
        'MeasureClassifAUC.R' 'MeasureClassifCE.R'
        'MeasureClassifConfusion.R' 'MeasureClassifCosts.R'
        'MeasureClassifF1.R' 'MeasureElapsedTime.R' 'MeasureOOBError.R'
        'MeasureRegr.R' 'MeasureRegrMAE.R' 'MeasureRegrMSE.R'
        'MeasureRegrRMSE.R' 'MeasureSelectedFeatures.R' 'Prediction.R'
        'PredictionClassif.R' 'PredictionRegr.R' 'ResampleResult.R'
        'Resampling.R' 'mlr_resamplings.R' 'ResamplingBootstrap.R'
        'ResamplingCV.R' 'ResamplingCustom.R' 'ResamplingHoldout.R'
        'ResamplingRepeatedCV.R' 'ResamplingSubsampling.R' 'Task.R'
        'TaskSupervised.R' 'TaskClassif.R' 'mlr_tasks.R'
        'TaskClassif_german_credit.R' 'TaskClassif_iris.R'
        'TaskClassif_pima.R' 'TaskClassif_sonar.R' 'TaskClassif_spam.R'
        'TaskClassif_wine.R' 'TaskClassif_zoo.R' 'TaskRegr.R'
        'TaskRegr_boston_housing.R' 'TaskRegr_mtcars.R'
        'Task_mutators.R' 'as_data_backend.R' 'assertions.R'
        'benchmark.R' 'cast_from_dict.R' 'expand_grid.R'
        'helper-parallelization.R' 'helper.R' 'mlr_control.R'
        'reexports.R' 'resample.R' 'worker.R' 'zzz.R'
Packaged: 2019-07-25 07:22:53 UTC; lang
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>),
  Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>),
  Jakob Richter [aut] (<https://orcid.org/0000-0003-4481-5554>),
  Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>),
  Giuseppe Casalicchio [ctb] (<https://orcid.org/0000-0001-5324-5966>),
  Stefan Coors [ctb] (<https://orcid.org/0000-0002-7465-2146>),
  Quay Au [ctb] (<https://orcid.org/0000-0002-5252-8902>),
  Martin Binder [aut]
Maintainer: Michel Lang <michellang@gmail.com>
Repository: CRAN
Date/Publication: 2019-07-25 14:10:02 UTC
