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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: | 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 |
| Reference manual: | mvs.pdf |
| 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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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.