sivs: Seed Independent Variable Selection

An iterative feature selection method (manuscript submitted) that internally utilizes various Machine Learning methods that have embedded feature reduction in order to shrink down the feature space into a small and yet robust set.

Version: 0.2.2
Imports: doParallel, parallel, foreach, glmnet, pROC, varhandle, utils
Suggests: knitr, rmarkdown, markdown
Published: 2020-10-06
Author: Mehrad Mahmoudian ORCID iD [aut, cre], Mikko Venäläinen ORCID iD [aut, rev], Riku Klèn ORCID iD [aut, ths], Laura Elo ORCID iD [aut, ths, fnd]
Maintainer: Mehrad Mahmoudian <mehrad.mahmoudian at>
License: GPL-3
NeedsCompilation: no
CRAN checks: sivs results


Reference manual: sivs.pdf
Vignettes: Seed Independent Variable Selection (SIVS)
Package source: sivs_0.2.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: sivs_0.2.2.tgz, r-oldrel: sivs_0.2.2.tgz


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