Package: rnnmf 0.3.0.0001

rnnmf: Regularized Non-Negative Matrix Factorization

A proof of concept implementation of regularized non-negative matrix factorization optimization. A non-negative matrix factorization factors non-negative matrix Y approximately as L R, for non-negative matrices L and R of reduced rank. This package supports such factorizations with weighted objective and regularization penalties. Allowable regularization penalties include L1 and L2 penalties on L and R, as well as non-orthogonality penalties. This package provides multiplicative update algorithms, which are a modification of the algorithm of Lee and Seung (2001) <http://papers.nips.cc/paper/1861-algorithms-for-non-negative-matrix-factorization.pdf>, as well as an additive update derived from that multiplicative update. See also Pav (2024) <doi:10.48550/arXiv.2410.22698>.

Authors:Steven E. Pav [aut, cre]

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rnnmf.pdf |rnnmf.html
rnnmf/json (API)

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

Bug tracker:https://github.com/shabbychef/rnnmf/issues

On CRAN:

Conda:

4.54 score 4 scripts 546 downloads 4 exports 2 dependencies

Last updated 1 months agofrom:6fbf3528a2. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 05 2025
R-4.5-winOKMar 05 2025
R-4.5-macOKMar 05 2025
R-4.5-linuxOKMar 05 2025
R-4.4-winOKMar 05 2025
R-4.4-macOKMar 05 2025
R-4.4-linuxOKMar 05 2025
R-4.3-winOKMar 05 2025
R-4.3-macOKMar 05 2025

Exports:aurnmfgaurnmfgiqpmmurnmf

Dependencies:latticeMatrix

An Iterative Algorithm for Regularized Non-negative Matrix Factorizations

Rendered fromrnnmf.Rnwusingknitr::knitron Mar 05 2025.

Last update: 2024-10-31
Started: 2024-10-24