FeatureTerminatoR: Feature Selection Engine to Remove Features with Minimal Predictive Power

The aim is to take in data.frame inputs and utilises methods, such as recursive feature engineering, to enable the features to be removed. What this does differently from the other packages, is that it gives you the choice to remove the variables manually, or it automated this process. Feature selection is a concept in machine learning, and statistical pipelines, whereby unimportant, or less predictive variables are eliminated from the analysis, see Boughaci (2018) <doi:10.1007/s40595-018-0107-y>.

Version: 1.0.0
Imports: ggplot2, caret, tibble, dplyr, stats, utils, lattice, e1071, randomForest
Suggests: knitr, markdown, rmarkdown
Published: 2021-07-14
Author: Gary Hutson ORCID iD [aut, cre]
Maintainer: Gary Hutson <hutsons-hacks at outlook.com>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
CRAN checks: FeatureTerminatoR results


Reference manual: FeatureTerminatoR.pdf
Vignettes: FeatureTerminatoR


Package source: FeatureTerminatoR_1.0.0.tar.gz
Windows binaries: r-devel: FeatureTerminatoR_1.0.0.zip, r-release: FeatureTerminatoR_1.0.0.zip, r-oldrel: FeatureTerminatoR_1.0.0.zip
macOS binaries: r-release (arm64): FeatureTerminatoR_1.0.0.tgz, r-release (x86_64): FeatureTerminatoR_1.0.0.tgz, r-oldrel: FeatureTerminatoR_1.0.0.tgz

Reverse dependencies:

Reverse suggests: ConfusionTableR


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