nnmf-package

Nonnegative matrix factorization (NMF) is implemented.

Nonnegative matrix factorization (NMF) is a technique to factorize a matrix with nonnegative values into the product of two matrices. Covariates are also allowed. Parallel computing is an option to enhance the speed and high-dimensional and large scale (and/or sparse) data are allowed. Relevant papers include: Wang Y. X. and Zhang Y. J. (2012). Nonnegative matrix factorization: A comprehensive review. IEEE Transactions on Knowledge and Data Engineering, 25(6), 1336-1353 <doi:10.1109/TKDE.2012.51> and Kim H. and Park H. (2008). Nonnegative matrix factorization based on alternating nonnegativity constrained least squares and active set method. SIAM Journal on Matrix Analysis and Applications, 30(2), 713-730 <doi:10.1137/07069239X>.

Michail Tsagris

nnmf

Nonnegative Matrix Factorization

nnmf-package function

Michail Tsagris <a href="/link/mtsagris%40uoc.gr?package=nnmf&version=1.1" data-mini-rdoc="nnmf::mtsagris@uoc.gr">mtsagris@uoc.gr</a>.

Author

Michail Tsagris &lt;mtsagris@uoc.gr&gt;

Maintainers

Nonnegative Matrix Factorization — nnmf-package

Michail Tsagris <a href='mailto:mtsagris@uoc.gr'>mtsagris@uoc.gr</a>.

Package:	nnmf
Type:	Package
Version:	1.1
Date:	2026-02-03
License:	GPL-2

nnmf-package: Nonnegative Matrix Factorization

Description

Arguments

Author

Maintainers

Details

References