mlpack_nmf - non-negative matrix factorization

       For further information, including relevant papers, citations,  and  theory,  consult  the  documentation
       found at http://www.mlpack.org or included with your distribution of mlpack.

mlpack-4.5.1                                     29 January 2025                                   mlpack_nmf(1)

       This  program  performs  non-negative  matrix  factorization  on the given dataset, storing the resulting
       decomposed matrices in the specified files. For an input dataset V, NMF decomposes V into two matrices  W
       and H such that

       V = W * H

       where  all  elements in W and H are non-negative. If V is of size (n x m), then W will be of size (n x r)
       and H will be of size (r x m), where r is the rank of the factorization (specified by the  '--rank  (-r)'
       parameter).

       Optionally, the desired update rules for each NMF iteration can be chosen from the following list:

              •  multdist: multiplicative distance-based update rules (Lee and Seung 1999)

              •  multdiv: multiplicative divergence-based update rules (Lee and Seung 1999)

              •  als: alternating least squares update rules (Paatero and Tapper 1994)

       The  maximum  number  of  iterations  is  specified with '--max_iterations (-m)', and the minimum residue
       required for algorithm termination is specified with the '--min_residue (-e)' parameter.

       For example, to run NMF on the input matrix 'V.csv' using the 'multdist'  update  rules  with  a  rank-10
       decomposition  and  storing the decomposed matrices into 'W.csv' and 'H.csv', the following command could
       be used:

       $ mlpack_nmf--input_file V.csv --w_file W.csv --h_file H.csv --rank 10 --update_rules multdist

mlpack_nmf - non-negative matrix factorization

--help(-h)[bool]
              Default help info.

       --info[string]
              Print help on a specific option. Default value ''.

       --initial_h_file(-q)[unknown]
              Initial H matrix.

       --initial_w_file(-p)[unknown]
              Initial W matrix.

       --max_iterations(-m)[int]
              Number of iterations before NMF terminates (0 runs until convergence. Default value 10000.

       --min_residue(-e)[double]
              The minimum root mean  square  residue  allowed  for  each  iteration,  below  which  the  program
              terminates. Default value 1e-05.

       --seed(-s)[int]
              Random  seed.  If  0,  'std::time(NULL)'  is used.  Default value 0.  --update_rules (-u) [string]
              Update rules for each iteration; ( multdist | multdiv | als ). Default value 'multdist'.

       --verbose(-v)[bool]
              Display informational messages and the full list of parameters and timers at the end of execution.

       --version(-V)[bool]
              Display the version of mlpack.

--h_file(-H)[unknown]
              Matrix to save the calculated H to.

       --w_file(-W)[unknown]
              Matrix to save the calculated W to.

--input_file(-i)[unknown]
              Input dataset to perform NMF on.

       --rank(-r)[int]
              Rank of the factorization.

mlpack_nmf-iunknown-rint [-qunknown] [-punknown] [-mint] [-edouble] [-sint] [-ustring] [-Vbool] [-Hunknown] [-Wunknown] [-h-v]