NAME

       mlpack_preprocess_one_hot_encoding - one hot encoding

SYNOPSIS

        mlpack_preprocess_one_hot_encoding -i string [-d vector] [-V bool] [-o unknown] [-h -v]

DESCRIPTION

       This  utility  takes  a  dataset  and a vector of indices and does one-hot encoding of the
       respective features at those indices. Indices represent the IDs of the  dimensions  to  be
       one-hot encoded.

       If  no  dimensions  are  specified  with  '--dimensions  (-d)',  then all categorical-type
       dimensions will be one-hot encoded. Otherwise, only the dimensions given in  '--dimensions
       (-d)' will be one-hot encoded.

       The  output  matrix  with  encoded  features  may  be  saved with the '--output_file (-o)'
       parameters.

       So, a simple example where we want to encode 1st and 3rd feature from dataset ’X.csv' into
       'X_output.csv' would be

       $   mlpack_preprocess_one_hot_encoding   --input_file   X.arff  --output_file  X_ouput.csv
       --dimensions 1 --dimensions 3

REQUIRED INPUT OPTIONS

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

OPTIONAL INPUT OPTIONS

       --dimensions (-d) [vector]
              Index  of  dimensions  that  need  to  be  one-hot  encoded  (if  unspecified,  all
              categorical dimensions are one-hot encoded). Default value [].

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

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

       --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.

OPTIONAL OUTPUT OPTIONS

       --output_file (-o) [unknown] Matrix to save one-hot encoded features data to.

ADDITIONAL INFORMATION

       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.