Variable Selection Oriented LASSO Bagging Algorithm

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) for more details.


Reference manual

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install.packages("VSOLassoBag")

1.0 by Chaoye Wang, a year ago


Browse source code at https://github.com/cran/VSOLassoBag


Authors: Jiaqi Liang [aut] , Chaoye Wang [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Imports glmnet, survival, ggplot2, POT, parallel, utils, pbapply, methods, SummarizedExperiment

Suggests rmarkdown, knitr, rmdformats, qpdf


See at CRAN