The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

UBayFS: A User-Guided Bayesian Framework for Ensemble Feature Selection

The framework proposed in Jenul et al., (2022) <doi:10.1007/s10994-022-06221-9>, together with an interactive Shiny dashboard. 'UBayFS' is an ensemble feature selection technique embedded in a Bayesian statistical framework. The method combines data and user knowledge, where the first is extracted via data-driven ensemble feature selection. The user can control the feature selection by assigning prior weights to features and penalizing specific feature combinations. 'UBayFS' can be used for common feature selection as well as block feature selection.

Version: 1.0
Depends: R (≥ 3.5.0)
Imports: DirichletReg, GA, ggplot2, gridExtra, hyper2, matrixStats, methods, mRMRe, Rdimtools, shiny, utils
Suggests: caret, dplyr, DT, glmnet, GSelection, knitr, plyr, RColorBrewer, rmarkdown, rpart, shinyalert, shinyBS, shinyjs, shinyWidgets, testthat (≥ 3.0.0)
Published: 2023-03-07
DOI: 10.32614/CRAN.package.UBayFS
Author: Anna Jenul ORCID iD [aut, cre], Stefan Schrunner ORCID iD [aut], Kristian Hovde Liland [rev], Oliver Tomic [ctb], Jürgen Pilz [ctb]
Maintainer: Anna Jenul <anna.jenul at nmbu.no>
BugReports: https://github.com/annajenul/UBayFS/issues
License: GPL-3
URL: https://annajenul.github.io/UBayFS/, https://joss.theoj.org/papers/10.21105/joss.04848
NeedsCompilation: no
CRAN checks: UBayFS results

Documentation:

Reference manual: UBayFS.pdf
Vignettes: UBayFS block feature selection
UBayFS

Downloads:

Package source: UBayFS_1.0.tar.gz
Windows binaries: r-devel: UBayFS_1.0.zip, r-release: UBayFS_1.0.zip, r-oldrel: UBayFS_1.0.zip
macOS binaries: r-release (arm64): UBayFS_1.0.tgz, r-oldrel (arm64): UBayFS_1.0.tgz, r-release (x86_64): UBayFS_1.0.tgz, r-oldrel (x86_64): UBayFS_1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=UBayFS to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.