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:Daniel Conn [aut, cre], Tuck Ngun [aut], Christina M. Ramirez [aut]

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fuzzyforest/json (API)

# Install 'fuzzyforest' in R:
install.packages('fuzzyforest', repos = c('https://daniel-conn17.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • Liver_Expr - Liver Expression Data from Female Mice
  • ctg - Cardiotocography Data Set
  • example_ff - Fuzzy Forest Example

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.35 score 45 scripts 337 downloads 1 mentions 9 exports 34 dependencies

Last updated 5 years agofrom:d8ddfad693. Checks:OK: 6 WARNING: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 16 2024
R-4.5-winOKNov 16 2024
R-4.5-linuxWARNINGNov 16 2024
R-4.4-winOKNov 16 2024
R-4.4-macOKNov 16 2024
R-4.3-winOKNov 16 2024
R-4.3-macOKNov 16 2024

Exports:fffuzzy_forestiterative_RFmodplotscreen_controlselect_controlselect_RFwffWGCNA_control

Dependencies:clicodetoolscolorspacedoParallelfansifarverforeachggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellmvtnormnlmepillarpkgconfigR6randomForestRColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr