linxihui/NNLM: Fast and Versatile Non-Negative Matrix Factorization

This is a package for Non-Negative Linear Models (NNLM). It implements fast sequential coordinate descent algorithms for non-negative linear regression and non-negative matrix factorization (NMF). It supports mean square error and Kullback-Leibler divergence loss. Many other features are also implemented, including missing value imputation, domain knowledge integration, designable W and H matrices and multiple forms of regularizations.

Getting started

Package details

LicenseBSD_2_clause + file LICENSE
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
linxihui/NNLM documentation built on March 8, 2021, 7:43 a.m.