Package: mvs 2.1.0
Wouter van Loon
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>.
Authors:
mvs_2.1.0.tar.gz
mvs_2.1.0.zip(r-4.7)mvs_2.1.0.zip(r-4.6)mvs_2.1.0.zip(r-4.5)
mvs_2.1.0.tgz(r-4.6-any)mvs_2.1.0.tgz(r-4.5-any)
mvs_2.1.0.tar.gz(r-4.7-any)mvs_2.1.0.tar.gz(r-4.6-any)
mvs_2.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
mvs/json (API)
NEWS
| # Install 'mvs' in R: |
| install.packages('mvs', repos = c('https://marjoleinf.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://gitlab.com/wsvanloon/mvs
Last updated from:dc383ff31e. Checks:9 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 245 | ||
| source / vignettes | OK | 231 | ||
| linux-release-x86_64 | OK | 218 | ||
| macos-release-arm64 | OK | 180 | ||
| macos-oldrel-arm64 | OK | 156 | ||
| windows-devel | OK | 194 | ||
| windows-release | OK | 187 | ||
| windows-oldrel | OK | 210 | ||
| wasm-release | OK | 118 |
Exports:mrmMRMmvsMVSRFstaplrStaPLR
Dependencies:codetoolsforeachglmnetiteratorslatticeMatrixrandomForestRcppRcppEigenshapesurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| mvs: Methods for High-Dimensional Multi-View Learning. | mvs-package |
| Extract coefficients from an "MVS" object. | coef.MVS |
| Extract coefficients from a "StaPLR" object. | coef.StaPLR |
| Calculate feature importance from an "MVS" object. | importance.MVS |
| Minority Report Measure | MRM mrm |
| Multi-View Stacking | MVS mvs |
| Make predictions from an "MVS" object. | predict.MVS |
| Make predictions from a "StaPLR" object. | predict.StaPLR |
| Make predictions from a "StaPLRcoef" object. | predict.StaPLRcoef |
| Function for fitting random forests with multi-view stacking | RF |
| Stacked Penalized Logistic Regression | StaPLR staplr |