DNMF: Discriminant Non-Negative Matrix Factorization

Share:

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.

Author
Zhilong Jia [aut, cre], Xiang Zhang [aut]
Date of publication
2015-06-09 21:29:09
Maintainer
Zhilong Jia <zhilongjia@gmail.com>
License
GPL (>= 2)
Version
1.3
URLs

View on CRAN

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.

Files in this package

DNMF
DNMF/NAMESPACE
DNMF/NEWS.md
DNMF/R
DNMF/R/NMFpval.R
DNMF/R/rnk.R
DNMF/R/DNMF.R
DNMF/R/ndNMF.R
DNMF/MD5
DNMF/DESCRIPTION
DNMF/man
DNMF/man/NMFpval.Rd
DNMF/man/ndNMF.Rd
DNMF/man/DNMF.Rd
DNMF/man/rnk.Rd