TDMR: Tuned Data Mining in R

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>.

Version: 2.0
Depends: R (≥ 2.14.0), SPOT (≥ 2.0), twiddler
Imports: testit, methods, adabag
Suggests: cmaes, parallel, e1071, powell, ROCR, randomForest, rCMA, rSFA
Published: 2018-05-04
Author: Wolfgang Konen, Patrick Koch
Maintainer: Wolfgang Konen <wolfgang.konen at fh-koeln.de>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: TDMR results

Downloads:

Reference manual: TDMR.pdf
Package source: TDMR_2.0.tar.gz
Windows binaries: r-devel: TDMR_2.0.zip, r-release: TDMR_2.0.zip, r-oldrel: TDMR_2.0.zip
OS X binaries: r-release: TDMR_2.0.tgz, r-oldrel: not available
Old sources: TDMR archive

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