Description Usage Arguments Value References
Implementation of the updates for the LSNMF algorithm from Wang et al. (2006).
wrss
implements the objective function used by the
LSNMF algorithm.
1 2 3 4 5 6 7 8  nmf_update.lsnmf(i, X, object, weight, eps = 10^9, ...)
wrss(object, X, weight)
nmfAlgorithm.lsNMF(..., .stop = NULL,
maxIter = nmf.getOption("maxIter") %% 2000, weight,
eps = 10^9, stationary.th = .Machine$double.eps,
check.interval = 5 * check.niter, check.niter = 10L)

i 
current iteration 
X 
target matrix 
object 
current NMF model 
weight 
value for S, i.e. the weights
that are applied to each entry in 
eps 
small number passed to the standard
euclideanbased NMF updates (see

... 
extra arguments (not used) 
.stop 
specification of a stopping criterion, that is used instead of the one associated to the NMF algorithm. It may be specified as:

maxIter 
maximum number of iterations to perform. 
stationary.th 
maximum absolute value of the gradient, for the objective function to be considered stationary. 
check.interval 
interval (in number of iterations) on which the stopping criterion is computed. 
check.niter 
number of successive iteration used to compute the stationnary criterion. 
updated object object
Wang G, Kossenkov AV and Ochs MF (2006). "LSNMF: a modified nonnegative matrix factorization algorithm utilizing uncertainty estimates." _BMC bioinformatics_, *7*, pp. 175. ISSN 14712105, <URL: http://dx.doi.org/10.1186/147121057175>, <URL: http://www.ncbi.nlm.nih.gov/pubmed/16569230>.
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