mlpack_nmf man page

mlpack_nmf ā€” non-negative matrix factorization

Synopsis

 mlpack_nmf [-h] [-v]  

Description

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 following list:

The maximum number of iterations is specified with --max_iterations, and the minimum residue required for algorithm termination is specified with --min_residue.

Required Input Options

--input_file (-i) [string]

Input dataset to perform NMF on.

--rank (-r) [int]

Rank of the factorization.

Optional Input Options

--help (-h)

Default help info.

--info [string]

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 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)

Display informational messages and the full list of parameters and timers at the end of execution.

--version (-V)

Display the version of mlpack.

Optional Output Options

--h_file (-H) [string]

File to save the calculated H matrix to. Default value ''.

--w_file (-W) [string]

File to save the calculated W matrix to. Default value ''.

Additional Information

Additional Information

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