Package: mlr3proba
Title: Probabilistic Supervised Learning for 'mlr3'
Version: 0.2.0
Authors@R: 
    c(person(given = "Raphael",
             family = "Sonabend",
             role = c("aut", "cre"),
             email = "raphael.sonabend.15@ucl.ac.uk",
             comment = c(ORCID = "0000-0001-9225-4654")),
      person(given = "Franz",
             family = "Kiraly",
             role = "aut",
             email = "f.kiraly@ucl.ac.uk"),
      person(given = "Michel",
             family = "Lang",
             role = "aut",
             email = "michellang@gmail.com",
             comment = c(ORCID = "0000-0001-9754-0393")),
      person(given = "Nurul Ain",
             family = "Toha",
             role = "ctb",
             email = "nurul.toha.15@ucl.ac.uk"),
      person(given="Andreas",
             family="Bender",
             email="bender.at.R@gmail.com",
             role = "ctb",
             comment=c(ORCID = "0000-0001-5628-8611")))
Description: Provides extensions for probabilistic supervised
    learning for 'mlr3'.  This includes extending the regression task to
    probabilistic and interval regression, adding a survival task, and
    other specialized models, predictions, and measures.
License: LGPL-3
URL: https://mlr3proba.mlr-org.com,
        https://github.com/mlr-org/mlr3proba
BugReports: https://github.com/mlr-org/mlr3proba/issues
Depends: R (>= 3.1.0)
Imports: checkmate, data.table, distr6 (>= 1.4.2), mlr3 (>= 0.3.0),
        mlr3misc (>= 0.1.7), mlr3pipelines, paradox (>= 0.1.0), Rcpp
        (>= 1.0.4), R6, survival
Suggests: bibtex, ggplot2, knitr, lgr, Matrix, mlr3tuning, pracma,
        rmarkdown, rpart, set6 (>= 0.1.7), simsurv, survAUC, testthat
LinkingTo: Rcpp
VignetteBuilder: knitr
ByteCompile: true
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
RoxygenNote: 7.1.0.9000
RdMacros: mlr3misc
Collate: 'LearnerDens.R' 'LearnerDensHistogram.R' 'LearnerDensKDE.R'
        'LearnerProbreg.R' 'LearnerProbregGaussian.R' 'LearnerSurv.R'
        'LearnerSurvCoxPH.R' 'LearnerSurvKaplan.R' 'LearnerSurvRpart.R'
        'MeasureDens.R' 'MeasureDensLogloss.R' 'MeasureRegrLogloss.R'
        'MeasureSurv.R' 'MeasureSurvIntegrated.R' 'MeasureSurvAUC.R'
        'MeasureSurvBeggC.R' 'MeasureSurvCalibrationAlpha.R'
        'MeasureSurvCalibrationBeta.R' 'MeasureSurvChamblessAUC.R'
        'MeasureSurvCindex.R' 'MeasureSurvGonenHellersC.R'
        'MeasureSurvGraf.R' 'MeasureSurvGrafSE.R'
        'MeasureSurvHarrellC.R' 'MeasureSurvHungAUC.R'
        'MeasureSurvIntLogloss.R' 'MeasureSurvIntLoglossSE.R'
        'MeasureSurvLogloss.R' 'MeasureSurvLoglossSE.R'
        'MeasureSurvMAE.R' 'MeasureSurvMAESE.R' 'MeasureSurvMSE.R'
        'MeasureSurvMSESE.R' 'MeasureSurvNagelkR2.R'
        'MeasureSurvOQuigleyR2.R' 'MeasureSurvRMSE.R'
        'MeasureSurvRMSESE.R' 'MeasureSurvSchmid.R'
        'MeasureSurvSongAUC.R' 'MeasureSurvSongTNR.R'
        'MeasureSurvSongTPR.R' 'MeasureSurvUnoAUC.R'
        'MeasureSurvUnoC.R' 'MeasureSurvUnoTNR.R' 'MeasureSurvUnoTPR.R'
        'MeasureSurvXuR2.R' 'PipeOpCrankCompositor.R'
        'PipeOpDistrCompositor.R' 'PipeOpProbRegr.R' 'PipeOpSurvAvg.R'
        'PredictionDens.R' 'PredictionProbreg.R' 'PredictionRegr.R'
        'PredictionSurv.R' 'RcppExports.R' 'TaskDens.R'
        'TaskDens_faithful.R' 'TaskDens_precip.R'
        'TaskGeneratorSimdens.R' 'TaskGeneratorSimsurv.R'
        'TaskProbreg.R' 'TaskSurv.R' 'TaskSurv_lung.R'
        'TaskSurv_rats.R' 'TaskSurv_unemployment.R' 'assertions.R'
        'cindex.R' 'crank_compositor.R' 'distr_compositor.R'
        'helpers.R' 'histogram.R' 'integrated_scores.R' 'pecs.R'
        'plot.R' 'probregr_compose.R' 'surv_average.R'
        'surv_measures.R' 'zzz.R'
Packaged: 2020-07-25 08:40:10 UTC; raphael
Author: Raphael Sonabend [aut, cre] (<https://orcid.org/0000-0001-9225-4654>),
  Franz Kiraly [aut],
  Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>),
  Nurul Ain Toha [ctb],
  Andreas Bender [ctb] (<https://orcid.org/0000-0001-5628-8611>)
Maintainer: Raphael Sonabend <raphael.sonabend.15@ucl.ac.uk>
Repository: CRAN
Date/Publication: 2020-07-25 21:10:02 UTC
