DNMF: Discriminant Non-Negative Matrix Factorization

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.

Version: 1.3
Depends: foreach
Imports: Matrix, gplots, parallel, doParallel
Published: 2015-06-09
Author: Zhilong Jia [aut, cre], Xiang Zhang [aut]
Maintainer: Zhilong Jia <zhilongjia at gmail.com>
BugReports: https://github.com/zhilongjia/DNMF/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/zhilongjia/DNMF
NeedsCompilation: no
Materials: NEWS
CRAN checks: DNMF results

Downloads:

Reference manual: DNMF.pdf
Package source: DNMF_1.3.tar.gz
Windows binaries: r-devel: DNMF_1.3.zip, r-release: DNMF_1.3.zip, r-oldrel: DNMF_1.3.zip
OS X El Capitan binaries: r-release: DNMF_1.3.tgz
OS X Mavericks binaries: r-oldrel: DNMF_1.3.tgz
Old sources: DNMF archive

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