Discriminant Non-Negative Matrix Factorization

Discriminant Non-Negative Matrix Factorization is 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. Two kinds of Discriminant Non-Negative Matrix Factorization were implemented so far.

Installation:

devtools::install_github("zhilongjia/DNMF")

Citation:

Jia Z, Zhang X, Guan N, Bo X, Barnes MR, Luo Z (2015) Gene Ranking of RNA-Seq Data via Discriminant Non-Negative Matrix Factorization. PLoS ONE 10(9): e0137782. doi:10.1371/journal.pone.0137782

Reference:

• 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.
• 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.