Boruta: Wrapper Algorithm for All Relevant Feature Selection

An all relevant feature selection wrapper algorithm. It finds relevant features by comparing original attributes' importance with importance achievable at random, estimated using their permuted copies (shadows).

Version: 6.0.0
Depends: ranger
Suggests: mlbench, rFerns, randomForest, testthat, xgboost
Published: 2018-07-17
Author: Miron Bartosz Kursa ORCID iD [aut, cre], Witold Remigiusz Rudnicki [aut]
Maintainer: Miron Bartosz Kursa <M.Kursa at icm.edu.pl>
BugReports: https://notabug.org/mbq/Boruta/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://notabug.org/mbq/Boruta/
NeedsCompilation: no
Citation: Boruta citation info
Materials: NEWS
In views: MachineLearning
CRAN checks: Boruta results

Downloads:

Reference manual: Boruta.pdf
Vignettes: Boruta for those in a hurry
Package source: Boruta_6.0.0.tar.gz
Windows binaries: r-devel: Boruta_6.0.0.zip, r-release: Boruta_6.0.0.zip, r-oldrel: Boruta_6.0.0.zip
OS X binaries: r-release: Boruta_6.0.0.tgz, r-oldrel: Boruta_6.0.0.tgz
Old sources: Boruta archive

Reverse dependencies:

Reverse suggests: fscaret, varrank

Linking:

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