Description Usage Arguments Value
Perform clustering of count data using the MMPCA model.
1 2 3 4 5 6 7 8 9 10 11 12 13 14  mmpca_clust(
dtm,
Q,
K,
model = NULL,
Yinit = "random",
method = "BBCVEM",
init.beta = "lda",
keep = 1L,
max.epochs = 10L,
verbose = 1L,
nruns = 1L,
mc.cores = max(1, (detectCores()  1))
)

dtm 
an NxV 
Q 
The number of clusters 
K 
The number of topics (latent space dimension) 
model 
A given model in which to take the controls for the VEsteps in
the greedy procedure. If NULL, a model of class

Yinit 
Parameter for the initialization of Y. It can be either:

method 
The clustering algorithm to be used. Only "BBCVEM" is available : it corresponds to the branch and bound CVEM of the original article. 
init.beta 
Parameter for the initialization of the matrix beta. It can be either:

keep 
The evolution of the bound is tracked every 
max.epochs 
Specifies the maximum number of pass allowed on the whole dataset. 
verbose 
verbosity level 
nruns 
number of runs of the algorithm (default to 1) : the run achieving the best evidence lower bound is selected. 
mc.cores 
The number of CPUs to use when fitting in parallel the different models (only for nonWindows platforms). Default is the number of available cores minus 1. 
An object of class "mmpcaClust"
containing the
fitted model.
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