Package: TDMR
Type: Package
Title: Tuned Data Mining in R
Version: 2.2
Date: 2020-03-01
Author: Wolfgang Konen <wolfgang.konen@fh-koeln.de>, Patrick Koch
    <patrick.koch@fh-koeln.de>
Maintainer: Wolfgang Konen <wolfgang.konen@fh-koeln.de>
Description: Tuned Data Mining in R ('TDMR') performs the complete tuning of a 
    data mining task (predictive analytics, that is classification and regression). 
    Preprocessing parameters and modeling parameters can be tuned simultaneously. 
    It incorporates a variety of tuners (among them 'SPOT' and 'CMA' with package 'rCMA') and 
    allows integration of additional tuners. Noise handling in the data mining optimization  
    process is supported, see Koch et al. (2015) <doi:10.1016/j.asoc.2015.01.005>.
License: GPL (>= 2)
Depends: R (>= 3.0.0), SPOT (>= 2.0), twiddler
Suggests: cmaes, parallel, e1071, ROCR, randomForest, rCMA, rSFA
Imports: testit, methods, adabag
Collate: 'defaultSC.R' 'defaultOpts.R' 'makeTdmRandomSeed.r'
        'printTDMclassifier.r' 'printTDMregressor.r' 'tdmBigLoop.r'
        'tdmClassify.r' 'tdmClassifyLoop.r' 'tdmDefaultsFill.r'
        'tdmDispatchTuner.r' 'tdmEnvTMakeNew.r' 'tdmGeneralUtils.r'
        'tdmGraphicUtils.r' 'tdmMapDesign.r' 'tdmMetacostRf.r'
        'tdmModelingUtils.r' 'tdmOptsDefaults.r' 'tdmParaBootstrap.r'
        'tdmPreprocUtils.r' 'tdmReadAndSplit.r' 'tdmReadDataset.r'
        'tdmRegress.r' 'tdmRegressLoop.r' 'tdmROCR.r' 'tdmStartSpot2.r'
        'tdmStartOther.r' 'tdmTuneIt.r' 'unbiasedRun.r'
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-03-02 16:46:49 UTC; wolfgang
Repository: CRAN
Date/Publication: 2020-03-02 17:20:02 UTC
Built: R 3.6.0; ; 2020-03-03 20:43:07 UTC; unix
