run_iNMF_tensor: Integrative NMF

In hdsu-bioquant/ButchR: Non-Negative Matrix Factorization Suite

Integrative NMF

Description

Computes integrative NMF on tensorflow using the reticulate framework, uses a list of non-negative matrices as input

Usage

run_iNMF_tensor(
  matrix_list,
  ranks = 2,
  n_initializations = 10,
  iterations = 10^4,
  convergence_threshold = 40,
  Sp = 0,
  lamb = 10,
  extract_features = FALSE
)

Arguments

matrix_list	List of non-negative matrices
ranks	numeric vector with ranks to factorize
n_initializations	Number of initializations to evaluate
iterations	Maximum number of iterations to run for every initialization
convergence_threshold	The factorization stops, if the convergence test is constant for this number of iterations
Sp	Sparsity,
lamb	Free parameter lambda bigger values shift the decomposition towards finding the common effect between niews.
extract_features	if TRUE performs feature extraction for all factorization ranks > 2.

Value

An object of class ButchR_integrativeNMF. containing a integrative H matrix and one W matrix for each input matrix

Examples

## Not run: 
inmf_exp <- run_iNMF_tensor(list(a = matrix(1:1000, ncol = 10),
                                    b = matrix(1:1000, ncol = 10)),
                               ranks = 2:5,
                               n_initializations     = 10,
                               iterations            = 10^4,
                               convergence_threshold = 40)
inmf_exp

## End(Not run)

hdsu-bioquant/ButchR documentation built on Jan. 28, 2023, 6:06 p.m.