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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: | 1.0.2 |
Depends: | glmnet (≥ 1.9-8) |
Imports: | foreach (≥ 1.4.4) |
Suggests: | testthat (≥ 3.0.0) |
Published: | 2023-08-15 |
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 |
Reference manual: | mvs.pdf |
Package source: | mvs_1.0.2.tar.gz |
Windows binaries: | r-devel: mvs_1.0.2.zip, r-release: mvs_1.0.2.zip, r-oldrel: mvs_1.0.2.zip |
macOS binaries: | r-release (arm64): mvs_1.0.2.tgz, r-oldrel (arm64): mvs_1.0.2.tgz, r-release (x86_64): mvs_1.0.2.tgz, r-oldrel (x86_64): mvs_1.0.2.tgz |
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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.
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