mlrCPO: Composable Preprocessing Operators and Pipelines for Machine Learning

Toolset that enriches 'mlr' with a diverse set of preprocessing operators. Composable Preprocessing Operators ("CPO"s) are first-class R objects that can be applied to data.frames and 'mlr' "Task"s to modify data, can be attached to 'mlr' "Learner"s to add preprocessing to machine learning algorithms, and can be composed to form preprocessing pipelines.

Version: 0.3.4
Depends: R (≥ 3.0.2), ParamHelpers (≥ 1.10), mlr (≥ 2.12)
Imports: BBmisc (≥ 1.11), stringi, checkmate (≥ 1.8.3), methods, stats, utils, backports (≥ 1.1.0)
Suggests: party, rpart, mlbench, knitr, rmarkdown, testthat, mRMRe, care, randomForestSRC, randomForest, ranger (≥ 0.8.0), Rfast, FSelector, e1071, DiscriMiner, digest, lintr, Hmisc, fastICA, rex
Published: 2018-07-02
Author: Martin Binder [aut, cre], Bernd Bischl [ctb], Michel Lang [ctb], Lars Kotthoff [ctb]
Maintainer: Martin Binder <ma.binder at>
License: BSD_2_clause + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mlrCPO results


Reference manual: mlrCPO.pdf
Vignettes: 1. First Steps
2. mlrCPO Core
3. Builtin CPOs
4. Custom CPOs
z 1. First Steps (No Output)
z 2. mlrCPO Core (No Output)
z 3. Builtin CPOs (No Output)
z 4. Custom CPOs (No Output)
Package source: mlrCPO_0.3.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: mlrCPO_0.3.4.tgz, r-oldrel: not available
Old sources: mlrCPO archive


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