Traditional noise filtering methods aim at removing noisy samples from a classification dataset. This package adapts classic and recent filtering techniques to be used in regression problems. To do this, it uses the approach proposed in Martin (2021) [<doi:10.1109/ACCESS.2021.3123151>]. Thus, the goal of the implemented noise filters is to eliminate samples with noise in regression datasets.
| Version: | 1.0.2 |
| Depends: | R (≥ 3.2.0) |
| Imports: | e1071, FNN, gbm, modelr, nnet, randomForest, rpart |
| Suggests: | testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: | 2022-03-10 |
| Author: | Juan Martin [aut, cre], José A. Sáez [aut], Emilio Corchado [aut], Pablo Morales [ctb] (Author of the NoiseFiltersR package), Julian Luengo [ctb] (Author of the NoiseFiltersR package), Luis P.F. Garcia [ctb] (Author of the NoiseFiltersR package), Ana C. Lorena [ctb] (Author of the NoiseFiltersR package), Andre C.P.L.F. de Carvalho [ctb] (Author of the NoiseFiltersR package), Francisco Herrera [ctb] (Author of the NoiseFiltersR package) |
| Maintainer: | Juan Martin <juanmartin at usal.es> |
| License: | GPL (≥ 3) |
| Copyright: | see file COPYRIGHTS |
| URL: | https://github.com/juanmartinsantos/regfilter |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | regfilter results |
| Reference manual: | regfilter.pdf |
| Vignettes: |
regfilter |
| Package source: | regfilter_1.0.2.tar.gz |
| Windows binaries: | r-devel: regfilter_1.0.2.zip, r-release: regfilter_1.0.2.zip, r-oldrel: regfilter_1.0.2.zip |
| macOS binaries: | r-release (arm64): regfilter_1.0.2.tgz, r-oldrel (arm64): regfilter_1.0.2.tgz, r-release (x86_64): regfilter_1.0.2.tgz, r-oldrel (x86_64): regfilter_1.0.2.tgz |
| Old sources: | regfilter archive |
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