Package: RBBR 0.1.0

Seyed Amir Malekpour

RBBR: Regression-Based Boolean Rule Inference

Tools for regression-based Boolean rule inference in artificial intelligence studies. The package fits ridge regression models on conjunction expansions and composes interpretable rule sets. Parallel execution is supported for multi-CPU environments.

Authors:Seyed Amir Malekpour [aut, cre]

RBBR_0.1.0.tar.gz
RBBR_0.1.0.zip(r-4.7)RBBR_0.1.0.zip(r-4.6)RBBR_0.1.0.zip(r-4.5)
RBBR_0.1.0.tgz(r-4.6-any)RBBR_0.1.0.tgz(r-4.5-any)
RBBR_0.1.0.tar.gz(r-4.7-any)RBBR_0.1.0.tar.gz(r-4.6-any)
RBBR_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
RBBR/json (API)

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

Bug tracker:https://github.com/compbioipm/rbbr/issues

Datasets:

On CRAN:

Conda:

3.18 score 143 downloads 3 exports 11 dependencies

Last updated from:5ee193a79c. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK120
source / vignettesOK182
linux-release-x86_64OK121
macos-release-arm64OK71
macos-oldrel-arm64OK112
windows-develOK79
windows-releaseOK73
windows-oldrelOK73
wasm-releaseOK115

Exports:rbbr_predictorrbbr_scalingrbbr_train

Dependencies:codetoolsdoParallelforeachglmnetiteratorslatticeMatrixRcppRcppEigenshapesurvival