DESCRIPTION

Package: predictiveModeling
Type: Package
Title: The predictive modeling package allows users to write custom
        predictive models or use off-the-shelf models via caret, and
        compare their performance.
Version: 0.12-5
Date: 2012-9-20
Author: Adam Margolin, Nicole Deflaux, Erhan Bilal
Maintainer: Sage Bionetworks Software Platform Team
        <platform@sagebase.org>
Description: The predictive modeling package allows users to write custom
    predictive models or use off-the-shelf models via caret, and compare their
    performance.
License: file LICENSE
Imports: methods, RColorBrewer
Depends: R(>= 2.13), foreach, caret, affy, survival, glmnet,
        randomSurvivalForest
Suggests: synapseClient, RUnit
Enhances: Rmpi
LazyLoad: no
LazyData: no
Collate: 'createAggregateFeatureDataSet.R' 'createENetTuneGrid.R'
        'createFeatureAndResponseDataList.R'
        'crossValidatePredictiveModel.R' 'defaultTrainControl.R'
        'filterPredictiveModelData.R' 'jet.colors.R'
        'plotPredictiveModelHeatmap.R' 'PredictiveModelPerformance.R'
        'PredictiveModelResults.R' 'testPackage.R' 'trainPartition.R'
        'zzz.R' 'PredictiveModelFeatureEvaluator.R'
        'filterNasFromMatrix.R' 'CaretModel.R' 'CoxModel.R'
        'GlmnetModel.R' 'LinearModel.R' 'MostCorrelatedFeatures.R'
        'PredictiveModel.R' 'convertDataFrameToFeatureMatrix.R'
        'crossValidatePredictiveSurvivalModel.R'
        'SurvivalModelPerformance.R' 'SurvivalModelPerformanceCV.R'
        'exactConcordanceIndex.R' 'RSFmodel.R' 'exactConcordanceIndexV.R'
Packaged: 2012-07-16 17:46:37 UTC; sagebio