DNMF: Discriminant Non-Negative Matrix Factorization
Version 1.3

Discriminant Non-Negative Matrix Factorization aims to extend the Non-negative Matrix Factorization algorithm in order to extract features that enforce not only the spatial locality, but also the separability between classes in a discriminant manner. It refers to three article, Zafeiriou, Stefanos, et al. "Exploiting discriminant information in nonnegative matrix factorization with application to frontal face verification." Neural Networks, IEEE Transactions on 17.3 (2006): 683-695. Kim, Bo-Kyeong, and Soo-Young Lee. "Spectral Feature Extraction Using dNMF for Emotion Recognition in Vowel Sounds." Neural Information Processing. Springer Berlin Heidelberg, 2013. and Lee, Soo-Young, Hyun-Ah Song, and Shun-ichi Amari. "A new discriminant NMF algorithm and its application to the extraction of subtle emotional differences in speech." Cognitive neurodynamics 6.6 (2012): 525-535.

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AuthorZhilong Jia [aut, cre], Xiang Zhang [aut]
Date of publication2015-06-09 21:29:09
MaintainerZhilong Jia <zhilongjia@gmail.com>
LicenseGPL (>= 2)
Version1.3
URL https://github.com/zhilongjia/DNMF
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("DNMF")

Man pages

DNMF: Discriminant Non-Negative Matrix Factorization.
ndNMF: a new discriminant Non-Negative Matrix Factorization (dNMF)
NMFpval: P value for discriminant Non-Negative Matrix Factorization
rnk: write rnk to a file from matrix W.

Functions

DNMF Man page Source code
NMFpval Man page Source code
ndNMF Man page Source code
rnk Man page Source code

Files

NAMESPACE
NEWS.md
R
R/NMFpval.R
R/rnk.R
R/DNMF.R
R/ndNMF.R
MD5
DESCRIPTION
man
man/NMFpval.Rd
man/ndNMF.Rd
man/DNMF.Rd
man/rnk.Rd
DNMF documentation built on May 19, 2017, 9:38 p.m.