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: | 7.0.0 |
| Imports: | ranger |
| Suggests: | mlbench, rFerns, randomForest, testthat, xgboost, survival |
| Published: | 2020-05-21 |
| Author: | Miron Bartosz Kursa
|
| Maintainer: | Miron Bartosz Kursa <M.Kursa at icm.edu.pl> |
| BugReports: | https://gitlab.com/mbq/Boruta/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://gitlab.com/mbq/Boruta/ |
| NeedsCompilation: | no |
| Citation: | Boruta citation info |
| Materials: | NEWS |
| In views: | MachineLearning |
| CRAN checks: | Boruta results |
| Reference manual: | Boruta.pdf |
| Vignettes: |
Boruta for those in a hurry |
| Package source: | Boruta_7.0.0.tar.gz |
| Windows binaries: | r-devel: Boruta_7.0.0.zip, r-release: Boruta_7.0.0.zip, r-oldrel: Boruta_7.0.0.zip |
| macOS binaries: | r-release: Boruta_7.0.0.tgz, r-oldrel: Boruta_7.0.0.tgz |
| Old sources: | Boruta archive |
| Reverse depends: | hsdar |
| Reverse imports: | immcp, smartdata |
| Reverse suggests: | fscaret, varrank |
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