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NNLM (version 0.4.3)

Fast and Versatile Non-Negative Matrix Factorization

Description

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.

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Install

install.packages('NNLM')

Monthly Downloads

17

Version

0.4.3

License

BSD_2_clause + file LICENSE

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Maintainer

Xihui Lin

Last Published

July 2nd, 2019

Functions in NNLM (0.4.3)

nnlm

Non-negative linear model/regression (NNLM)
mse.mkl

Compute mean square error(MSE) and mean kL divergence (MKL)
predict.nnmf

Methods for nnmf object returned by nnmf
nsclc

Micro-array data of NSCLC patients
nnmf

Non-negative matrix factorization