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mvs  

Methods for High-Dimensional Multi-View Learning
View on CRAN: Click here


Download and install mvs package within the R console
Install from CRAN:
install.packages("mvs")

Install from Github:
library("remotes")
install_github("cran/mvs")

Install by package version:
library("remotes")
install_version("mvs", "2.1.0")



Attach the package and use:
library("mvs")
Maintained by
Wouter van Loon
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-08-15
Latest Update: 2025-04-15
Description:
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) and Van Loon et al. (2022) .
How to cite:
Wouter van Loon (2023). mvs: Methods for High-Dimensional Multi-View Learning. R package version 2.1.0, https://cran.r-project.org/web/packages/mvs. Accessed 25 Aug. 2026.
Previous versions and publish date:
(2026-07-09 06:34), 1.0.2 (2023-08-15 13:00), 2.0.0 (2024-08-29 15:00)
Other packages that cited mvs R package
View mvs citation profile
Other R packages that mvs depends, imports, suggests or enhances
Complete documentation for mvs
Functions, R codes and Examples using the mvs R package
Some associated functions: MVS . StaPLR . coef.MVS . coef.StaPLR . mvs-package . predict.MVS . predict.StaPLR . predict.StaPLRcoef . 
Some associated R codes: MVS.R . StaPLR.R . condense.R . kFolds.R . learn.R .  Full mvs package functions and examples
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