Package summary | What is multi-view stacking? | Why package mvs? | Overview of package functionality | Model fitting | Parallelization | Model generalizations | View importance | Handling missing data | Using mvs step-by-step | Installation | Fitting a basic model | Random forests | Parallel computing | Fitting a model with more than two levels | Fitting a model with missing data | Acknowledgements | References
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.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✨
DESCRIPTION |NEWS
card.svg |card.png
mvs/json (API)
| # Install 'mvs' in R: |
| install.packages('mvs', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:3d04166501. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 219 | ||
| source / vignettes | OK | 227 | ||
| linux-release-x86_64 | OK | 220 | ||
| wasm-release | OK | 151 |
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 |