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VSOLassoBag (version 0.99.1)

Variable Selection Oriented LASSO Bagging Algorithm

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) for more details.

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Version

Install

install.packages('VSOLassoBag')

Monthly Downloads

180

Version

0.99.1

License

GPL-3

Maintainer

Chaoye Wang

Last Published

March 24th, 2023

Functions in VSOLassoBag (0.99.1)

ExpressionData

Simulated Example Data for VSOLassoBag Application
simpleEstimation

Parametric Statistical Test
VSOLassoBag

One-step main function of VSOLassoBag framework
LessPermutation

Reduce permutation times
kneedle

Kneedle Algorithm: to detect elbow point(s) on the curve