fuzzyforest
1.0.8Fuzzy Forests
Overview
Fuzzy forests, a new algorithm based on random forests, is designed to reduce the bias seen in random forest feature selection caused by the presence of correlated features. Fuzzy forests uses recursive feature elimination random forests to select features from separate blocks of correlated features where the correlation within each block of features is high and the correlation between blocks of features is low. One final random forest is fit using the surviving features. This package fits random forests using the 'randomForest' package and allows for easy use of 'WGCNA' to split features into distinct blocks. See D. Conn, Ngun, T., C. Ramirez, and G. Li (2019) doi:10.18637/jss.v091.i09 for further details.
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Health
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 87%
- Return-value docs
- 89%
- References docs
- 33%
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People & History
9 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 1.0.8Latest
- 1.0.72020-02-05 · diff ↗
- 1.0.62019-10-27 · diff ↗
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- 1.0.52018-02-03 · diff ↗
- 1.0.42017-11-12 · diff ↗
- 1.0.32017-06-11 · diff ↗
- RR 3.4.0 released · 2017-04-21
Package metadata
- First published
- 2016-02-18
- Total releases
- 9 / 10 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.2.1
- Bundled data
- 602 KB / 3 files
- Download size
- 651 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet