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rBMF: Boolean Matrix Factorization

Provides four boolean matrix factorization (BMF) methods. BMF has many applications like data mining and categorical data analysis. BMF is also known as boolean matrix decomposition (BMD) and was found to be an NP-hard (non-deterministic polynomial-time) problem. Currently implemented methods are 'Asso' Miettinen, Pauli and others (2008) <doi:10.1109/TKDE.2008.53>, 'GreConD' R. Belohlavek, V. Vychodil (2010) <doi:10.1016/j.jcss.2009.05.002> , 'GreConDPlus' R. Belohlavek, V. Vychodil (2010) <doi:10.1016/j.jcss.2009.05.002> , 'topFiberM' A. Desouki, M. Roeder, A. Ngonga (2019) <doi:10.48550/arXiv.1903.10326>.

Version: 1.1
Depends: R (≥ 3.2.0), Matrix, methods, Rcpp
Published: 2021-01-13
DOI: 10.32614/CRAN.package.rBMF
Author: Abdelmoneim Amer Desouki
Maintainer: Abdelmoneim Amer Desouki <desouki at hhu.de>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
CRAN checks: rBMF results

Documentation:

Reference manual: rBMF.pdf

Downloads:

Package source: rBMF_1.1.tar.gz
Windows binaries: r-devel: rBMF_1.1.zip, r-release: rBMF_1.1.zip, r-oldrel: rBMF_1.1.zip
macOS binaries: r-release (arm64): rBMF_1.1.tgz, r-oldrel (arm64): rBMF_1.1.tgz, r-release (x86_64): rBMF_1.1.tgz, r-oldrel (x86_64): rBMF_1.1.tgz
Old sources: rBMF archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.