Package: fuzzyforest 1.0.8
fuzzyforest: Fuzzy Forests
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.
Authors:
fuzzyforest_1.0.8.tar.gz
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fuzzyforest.pdf |fuzzyforest.html✨
fuzzyforest/json (API)
# Install 'fuzzyforest' in R: |
install.packages('fuzzyforest', repos = c('https://daniel-conn17.r-universe.dev', 'https://cloud.r-project.org')) |
- Liver_Expr - Liver Expression Data from Female Mice
- ctg - Cardiotocography Data Set
- example_ff - Fuzzy Forest Example
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:d8ddfad693. Checks:OK: 6 WARNING: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 16 2024 |
R-4.5-win | OK | Nov 16 2024 |
R-4.5-linux | WARNING | Nov 16 2024 |
R-4.4-win | OK | Nov 16 2024 |
R-4.4-mac | OK | Nov 16 2024 |
R-4.3-win | OK | Nov 16 2024 |
R-4.3-mac | OK | Nov 16 2024 |
Exports:fffuzzy_forestiterative_RFmodplotscreen_controlselect_controlselect_RFwffWGCNA_control
Dependencies:clicodetoolscolorspacedoParallelfansifarverforeachggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellmvtnormnlmepillarpkgconfigR6randomForestRColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr