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multiview  

Cooperative Learning for Multi-View Analysis
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("multiview", "1.0")



Attach the package and use:
library("multiview")
Maintained by
Balasubramanian Narasimhan
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-09-02
Latest Update: 2023-03-31
Description:
Cooperative learning combines the usual squared error loss of predictions with an agreement penalty to encourage the predictions from different data views to agree. By varying the weight of the agreement penalty, we get a continuum of solutions that include the well-known early and late fusion approaches. Cooperative learning chooses the degree of agreement (or fusion) in an adaptive manner, using a validation set or cross-validation to estimate test set prediction error. In the setting of cooperative regularized linear regression, the method combines the lasso penalty with the agreement penalty (Ding, D., Li, S., Narasimhan, B., Tibshirani, R. (2021) ).
How to cite:
Balasubramanian Narasimhan (2022). multiview: Cooperative Learning for Multi-View Analysis. R package version 1.0, https://cran.r-project.org/web/packages/multiview. Accessed 02 Nov. 2026.
Previous versions and publish date:
(2026-07-09 06:33), 0.4 (2022-09-02 10:00), 0.7 (2022-11-04 23:30), 0.8 (2023-03-31 22:10)
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Complete documentation for multiview
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