VSOLassoBag
1.0Variable Selection Oriented LASSO Bagging Algorithm
Overview
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.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-05-1013 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 2 earlier snapshots
- ERROR2026-05-0312 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 40%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
Datasets
People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.0Latest
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 0.99.12023-03-24 · diff ↗
- 0.99.02022-11-25
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2022-11-25
- Total releases
- 3 / 4 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.6.0
- Bundled data
- 764 KB / 1 file
- Download size
- 1.4 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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