NAME

       mlpack_radical - radical

SYNOPSIS

        mlpack_radical [-h] [-v]

DESCRIPTION

       An  implementation  of RADICAL, a method for independentcomponent analysis (ICA). Assuming
       that we have an input matrix X, thegoal is to find a square unmixing matrix W such that  Y
       =  W  *  X  and  the  dimensions  of  Y  are  independent  components. If the algorithm is
       runningparticularly slowly, try reducing the number of replicates.

REQUIRED INPUT OPTIONS

       --input_file (-i) [string]
              Input dataset filename for ICA.

OPTIONAL INPUT OPTIONS

       --angles (-a) [int]
              Number of angles to consider in brute-force search during Radical2D. Default  value
              150.

       --help (-h)
              Default help info.

       --info [string]
              Get  help  on a specific module or option.  Default value ''.  --noise_std_dev (-n)
              [double] Standard deviation of Gaussian noise. Default value 0.175.

       --objective (-O)
              If set, an estimate of the final objective function is printed.

       --replicates (-r) [int]
              Number of Gaussian-perturbed replicates to use (per point)  in  Radical2D.  Default
              value 30.

       --seed (-s) [int]
              Random seed. If 0, 'std::time(NULL)' is used.  Default value 0.

       --sweeps (-S) [int]
              Number  of  sweeps;  each  sweep  calls Radical2D once for each pair of dimensions.
              Default value

              0.

       --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

       --output_ic_file  (-o)  [string] File to save independent components to. Default value ''.
       --output_unmixing_file (-u) [string] File to save unmixing 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.

                                                                 mlpack_radical(16 November 2017)