NAME

       mlpack_preprocess_binarize - binarize data

SYNOPSIS

        mlpack_preprocess_binarize [-h] [-v]

DESCRIPTION

       This  utility  takes  a  dataset  and  binarizes  the  variables  into either 0 or 1 given
       threshold. User can apply binarization on a dimension or the whole  dataset.  A  dimension
       can  be  specified using --dimension (-d) option. Threshold can also be specified with the
       --threshold (-t) option; The default is 0.0.

       The program does not modify the original file, but instead makes a separate file  to  save
       the  binarized  data; The program requires you to specify the file name with --output_file
       (-o).

       For example, if we want to make all variables greater than 5 in dataset to 1 and ones that
       are less than or equal to 5.0 to 0, and save the result to result.csv, we could run

       $ mlpack_preprocess_binarize -i dataset.csv -t 5 -o result.csv

       But  if  we  want to apply this to only the first (0th) dimension of the dataset, we could
       run

       $ mlpack_preprocess_binarize -i dataset.csv -t 5 -d 0 -o result.csv

REQUIRED INPUT OPTIONS

       --input_file (-i) [string]
              File containing data.

OPTIONAL INPUT OPTIONS

       --dimension (-d) [int]
              Dimension to apply the binarization. If not set, the program  will  binarize  every
              dimension by default. Default value 0.

       --help (-h)
              Default help info.

       --info [string]
              Get help on a specific module or option.  Default value ''.

       --threshold (-t) [double]
              Threshold  to  be  applied  for binarization. If not set, the threshold defaults to
              0.0. 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_file (-o) [string]
              File to save the output. 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_preprocess_binarize(16 November 2017)