This is the command mlpack_nmf that can be run in the OnWorks free hosting provider using one of our multiple free online workstations such as Ubuntu Online, Fedora Online, Windows online emulator or MAC OS online emulator
mlpack_nmf - non-negative matrix factorization
mlpack_nmf [-h] [-v] -H string -i string -r int -W string [-m int] [-e double] [-s int] [-u string] -V
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 --rank).
Optionally, the desired update rules for each NMF iteration can be chosen from the
· 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, and the minimum
residue required for algorithm termination is specified with --min_residue.
--h_file (-H) [string]
File to save the calculated H matrix to.
--input_file (-i) [string]
Input dataset to perform NMF on.
--rank (-r) [int]
Rank of the factorization.
--w_file (-W) [string]
File to save the calculated W matrix to.
Default help info.
Get help on a specific module or option. Default value ''.
--max_iterations (-m) [int]
Number of iterations before NMF terminates (0 runs until convergence. Default value
--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'.
Display informational messages and the full list of parameters and timers at the
end of execution.
Display the version of mlpack.
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.
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