DESCRIPTION

Package: OnlineSuperLearner
Type: Package
Title: Online SuperLearner package
Version: 0.0.1
Date: 2017-01-25
Authors@R: c(person("Frank", "Blaauw", role=c("aut", "cre"), email="f.j.blaauw@rug.nl"),
             person("Antoine", "Chambaz", role=c("aut"), email="achambaz@u-paris10.fr"))
Maintainer: Frank Blaauw <f.j.blaauw@rug.nl>
Description: Package that enabling online super learning. This package runs a
    set of estimators and tries to find the conditional densities of relevantvariables
    provided to it. Then, using a set of machine learning algorithms, it will
    find the best convex combination of algorithms to predict these conditional
    densities.
License: MIT + file LICENSE
LazyLoad: yes
Encoding: UTF-8
LazyData: yes
Depends:
    R (>= 2.9.0),
    R6
Imports:
    parallel,
    data.table,
    R.utils (>= 1.4.1),
    h2o (>=	3.10.3.2),
    R.oo,
    R.methodsS3,
    condensier,
    methods,
    magrittr,
    MASS,
    Metrics,
    purrr,
    tidyverse,
    pROC,
    assertthat,
    xgboost,
    speedglm,
    randomForest,
    neuralnet,
    e1071,
    glmnet,
    future,
    RColorBrewer,
    foreach,
    doParallel,
    optimr,
    sgd,
    nnls,
    ggplot2,
    reshape2,
    jsonlite,
    dplyr,
    digest
Suggests:
    roxygen2,
    covr,
    testthat,
    mockery,
    devtools,
    knitr,
    rmarkdown
RoxygenNote: 6.1.1
Collate:
    'ConditionalDensityEvaluator.R'
    'ConstrainedGlm.R'
    'Evaluation.R'
    'CrossValidationRiskCalculator.R'
    'Data.Base.R'
    'Data.Static.R'
    'Data.Stream.R'
    'Simulator.Simple.R'
    'Data.Stream.Simulator.R'
    'DataCache.R'
    'DataSplitter.R'
    'DensityEstimation.R'
    'H2O.initializer.R'
    'H2O.Interactor.R'
    'InterventionParser.R'
    'InterventionEffectCalculator.R'
    'ML.SVM.R'
    'ML.randomForest.R'
    'ML.Local.lm.R'
    'ML.NeuralNet.R'
    'ML.Base.R'
    'ML.XGBoost.R'
    'ML.H2O.R'
    'LibraryFactory.R'
    'ML.GLMnet.R'
    'ML.H2O.gbm.R'
    'ML.H2O.glm.R'
    'ML.H2O.randomForest.R'
    'ML.SpeedGLMSGD.R'
    'RelevantVariable.R'
    'OneStepEstimator.R'
    'OnlineSuperLearner.Predict.R'
    'OnlineSuperLearner.S3.R'
    'OnlineSuperLearner.SampleIteratively.R'
    'WCC.SGD.Simplex.R'
    'WeightedCombinationComputer.R'
    'WCC.CG.R'
    'WCC.NMBFGS.R'
    'SMG.Mock.R'
    'SummaryMeasureGenerator.R'
    'zzz.R'
    'OnlineSuperLearner.R'
    'OutputPlotGenerator.R'
    'PreProcessor.R'
    'SMG.Base.R'
    'SMG.Lag.R'
    'SMG.Latest.Entry.R'
    'SMG.Mean.R'
    'SMG.Transformation.R'
    'SMGFactory.R'
    'Simulator.GAD.R'
    'Simulator.RunningExample.R'
    'Simulator.Slow.R'
    'WCC.NLopt.R'
    'WCC.NNLS.R'
    'WCC.SGD.R'
Remotes:
    github::osofr/condensier@fb-add-update,
    github::jimhester/covr,
    github::airoldilab/sgd,
    github::n-s-f/mockery@master
VignetteBuilder: knitr