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SVEMnet  

Self-Validated Ensemble Models with Elastic Net Regression
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("SVEMnet", "1.2.1")



Attach the package and use:
library("SVEMnet")
Maintained by
Andrew T. Karl
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-11-20
Latest Update: 2024-11-20
Description:
Implements Self-Validated Ensemble Models (SVEM, Lemkus et al. (2021) <doi:10.1016/j.chemolab.2021.104439>) using Elastic Net regression via 'glmnet' (Friedman et al. <doi:10.18637/jss.v033.i01>). SVEM averages predictions from multiple models fitted to fractionally weighted bootstraps of the data, tuned with anti-correlated validation weights. Also implements the randomized permutation whole model test for SVEM (Karl (2024) <doi:10.1016/j.chemolab.2024.105122>). Code for the whole model test was taken from the supplementary material of Karl (2024). Development of this package was assisted by 'GPT o1-preview' for code structure and documentation.
How to cite:
Andrew T. Karl (2024). SVEMnet: Self-Validated Ensemble Models with Elastic Net Regression. R package version 1.2.1, https://cran.r-project.org/web/packages/SVEMnet. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.0.3 (2024-11-20 11:30), 1.1.1 (2024-11-30 00:30), 1.2.1 (2024-12-07 21:10)
Other packages that cited SVEMnet R package
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Complete documentation for SVEMnet
Functions, R codes and Examples using the SVEMnet R package
Full SVEMnet package functions and examples
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