Package: ClassifyR
Type: Package
Title: A framework for cross-validated classification problems, with
        applications to differential variability and differential
        distribution testing
Version: 2.4.4
Date: 2019-06-14
Author: Dario Strbenac, John Ormerod, Graham Mann, Jean Yang
Maintainer: Dario Strbenac <dario.strbenac@sydney.edu.au>
VignetteBuilder: knitr
biocViews: Classification, Survival
Depends: R (>= 3.6.0), methods, S4Vectors, MultiAssayExperiment,
        BiocParallel
Imports: locfit, grid, utils, plyr
Suggests: limma, genefilter, edgeR, car, Rmixmod, ggplot2, gridExtra,
        cowplot, BiocStyle, pamr, PoiClaClu, parathyroidSE, knitr,
        htmltools, gtable, scales, e1071, rmarkdown, IRanges,
        randomForest, robustbase, glmnet, class
Description: The software formalises a framework for classification in R.
             There are four stages; Data transformation, feature selection, classifier training,
             and prediction. The requirements of variable types and names are
             fixed, but specialised variables for functions can also be provided.
             The classification framework is wrapped in a driver loop, that
             reproducibly carries out a number of cross-validation schemes.
             Functions for differential expression, differential variability,
             and differential distribution are included. Additional functions
             may be developed by the user, by creating an interface to the framework.
Collate: classes.R utilities.R bartlettSelection.R calcPerformance.R
        classifyInterface.R DLDAinterface.R DMDselection.R
        differentMeansSelection.R distribution.R edgeRselection.R
        edgesToHubNetworks.R elasticNetGLMinterface.R
        elasticNetFeatures.R featureSetSummary.R fisherDiscriminant.R
        forestFeatures.R getLocationsAndScales.R
        interactorDifferences.R kNNinterface.R
        KolmogorovSmirnovSelection.R KullbackLeiblerSelection.R
        kTSPclassifier.R leveneSelection.R likelihoodRatioSelection.R
        limmaSelection.R mixmodels.R naiveBayesKernel.R
        networkCorrelationsSelection.R NSCselectionInterface.R
        NSCtrainInterface.R NSCpredictInterface.R
        pairsDifferencesSelection.R performancePlot.R
        plotFeatureClasses.R previousSelection.R previousTrained.R
        randomForestInterface.R rankingPlot.R ROCplot.R runTest.R
        runTests.R samplesMetricMap.R selectionPlot.R
        subtractFromLocation.R SVMinterface.R
License: GPL-3
Packaged: 2019-06-15 03:06:39 UTC; biocbuild
git_url: https://git.bioconductor.org/packages/ClassifyR
git_branch: RELEASE_3_9
git_last_commit: a2993e1
git_last_commit_date: 2019-06-14
Date/Publication: 2019-06-14
NeedsCompilation: no
Built: R 3.6.0; ; 2019-06-15 12:49:16 UTC; windows
