mmpca_clust: Greedy procedures for joint inference and clustering in MMPCA

In MoMPCA: Inference and Clustering for Mixture of Multinomial Principal Component Analysis

Description

Perform clustering of count data using the MMPCA model.

Usage

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))
)

Arguments

dtm	an NxV DocumentTermMatrix with term-frequency weighting.
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 VE-steps in the greedy procedure. If NULL, a model of class mmpcaClust is created with default controls (see mmpcaClustcontrol class for more details).
Yinit	Parameter for the initialization of Y. It can be either: a string or a function specifying the initialization procedure. It should be one of ('random', 'kmeans_lda'). See benchmarks-functions functions for more details. A vector of length N with Q modalities, specifying the initialization clustering.
method	The clustering algorithm to be used. Only "BBCVEM" is available : it corresponds to the branch and bound C-VEM of the original article.
init.beta	Parameter for the initialization of the matrix beta. It can be either: a string specifying the initialization procedure. It should be one of ('random', 'lda'). See initializeBeta() for more details. A KxV matrix with each row summing to 1.
keep	The evolution of the bound is tracked every keep iteration
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 non-Windows platforms). Default is the number of available cores minus 1.

Value

An object of class "mmpcaClust" containing the fitted model.

MoMPCA documentation built on Jan. 21, 2021, 5:09 p.m.