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VSOLassoBag  

Variable Selection Oriented LASSO Bagging Algorithm
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("VSOLassoBag", "0.99.1")



Attach the package and use:
library("VSOLassoBag")
Maintained by
Chaoye Wang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-11-25
Latest Update: 2023-03-24
Description:
A wrapped LASSO approach by integrating an ensemble learning strategy to help select efficient, stable, and high confidential variables from omics-based data. Using a bagging strategy in combination of a parametric method or inflection point search method for cut-off threshold determination. This package can integrate and vote variables generated from multiple LASSO models to determine the optimal candidates. Luo H, Zhao Q, et al (2020) <doi:10.1126/scitranslmed.aax7533> for more details.
How to cite:
Chaoye Wang (2022). VSOLassoBag: Variable Selection Oriented LASSO Bagging Algorithm. R package version 0.99.1, https://cran.r-project.org/web/packages/VSOLassoBag. Accessed 27 Jan. 2025.
Previous versions and publish date:
0.99.0 (2022-11-25 13:50)
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Other R packages that VSOLassoBag depends, imports, suggests or enhances
Complete documentation for VSOLassoBag
Functions, R codes and Examples using the VSOLassoBag R package
Some associated functions: ExpressionData . LessPermutation . VSOLassoBag . kneedle . simpleEstimation . 
Some associated R codes: LessPermutation.R . PreFilter2.R . elbowDetection.R . gradient_descent.R . lassoBagAddGPD.R . pareto_simple_opt_func.R . simpleEstimation.R . simulated_example-data.R .  Full VSOLassoBag package functions and examples
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