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.

Install the latest version of this package by entering the following in R:
install.packages("NNLM")
AuthorXihui Lin [aut, cre], Paul C Boutros [aut]
Date of publication2016-01-03 22:50:42
MaintainerXihui Lin <xihuil.silence@gmail.com>
LicenseBSD_2_clause + file LICENSE
Version0.4.1
https://github.com/linxihui/NNLM

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Files

inst
inst/doc
inst/doc/Fast-And-Versatile-NMF.Rmd
inst/doc/Fast-And-Versatile-NMF.R
inst/doc/Fast-And-Versatile-NMF.html
tests
tests/testthat.R
tests/testthat
tests/testthat/test-nnmf.R tests/testthat/test-nnlm.R
src
src/Makevars
src/base_algorithms.cpp
src/update_with_missing.cpp
src/nnlm.cpp
src/nnlm.h
src/RcppExports.cpp
src/nnmf.cpp
NAMESPACE
NEWS
data
data/nsclc.rda
R
R/nnmf.R R/nnmf_methods.R R/nnlm.R R/misc.R R/pkgname.R
vignettes
vignettes/Fast-And-Versatile-NMF.Rmd
vignettes/ref.bib
MD5
build
build/vignette.rds
DESCRIPTION
man
man/mse.mkl.Rd man/predict.nnmf.Rd man/nnlm.Rd man/nsclc.Rd man/nnmf.Rd
LICENSE

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.