Description Usage Arguments Details Author(s) Examples
The ndNMF algorithm with the additional Fisher criterion on the cost function of conventional NMF was designed to increase class-related discriminating power.
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dat |
a matrix with gene in row and sample in column |
trainlabel |
the label of sample, like c(1,1,2,2,2) |
r |
the dimension of expected reduction dimension, with the default value 2 |
lambada |
a relative weighting factor for the discriminant. Default 0.1 |
maxIter |
the maximum iteration of update rules, with the default value 1000 |
tol |
the toleration of coverange, with the default value 1e-7 |
log |
log2 data. Default is TRUE. |
plotit |
whether plot H (V=WH). Default: FALSE. |
verbose |
TRUE |
... |
to gplots::heatmap.2 |
This algorithm is based on articles.
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.
Zhilong Jia and Xiang Zhang
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