mvs: Methods for High-Dimensional Multi-View Learning

Methods for high-dimensional multi-view learning based on the multi-view stacking (MVS) framework. For technical details on the MVS and stacked penalized logistic regression (StaPLR) methods see Van Loon, Fokkema, Szabo, & De Rooij (2020) <doi:10.1016/j.inffus.2020.03.007> and Van Loon et al. (2022) <doi:10.3389/fnins.2022.830630>.

Version: 2.0.0
Depends: glmnet (≥ 1.9-8)
Imports: foreach (≥ 1.4.4)
Suggests: testthat (≥ 3.0.0), mice (≥ 3.16.0), missForest (≥ 1.5)
Published: 2024-08-29
DOI: 10.32614/CRAN.package.mvs
Author: Wouter van Loon [aut, cre], Marjolein Fokkema [ctb]
Maintainer: Wouter van Loon <w.s.van.loon at fsw.leidenuniv.nl>
License: GPL-2
NeedsCompilation: no
Citation: mvs citation info
Materials: README NEWS
CRAN checks: mvs results

Documentation:

Reference manual: mvs.pdf

Downloads:

Package source: mvs_2.0.0.tar.gz
Windows binaries: r-devel: mvs_2.0.0.zip, r-release: mvs_2.0.0.zip, r-oldrel: mvs_2.0.0.zip
macOS binaries: r-release (arm64): mvs_2.0.0.tgz, r-oldrel (arm64): mvs_2.0.0.tgz, r-release (x86_64): mvs_2.0.0.tgz, r-oldrel (x86_64): mvs_2.0.0.tgz
Old sources: mvs archive

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