NAME

       mlpack_allkfn - all k-furthest-neighbors

SYNOPSIS

        mlpack_allkfn [-h] [-v] [-d string] [-m string] [-k int] [-l int] [-N] [-n string] [-M string] [-q string] [-R] [-r string] [--seed int] [-s] [-t string] -V

DESCRIPTION

       This  program  will  calculate  the  all k-furthest-neighbors of a set of points.  You may
       specify a separate set of reference points and query points, or just a reference set which
       will be used as both the reference and query set.

       For  example,  the  following  will  calculate  the  5  furthest neighbors of eachpoint in
       'input.csv' and store the distances in 'distances.csv'  and  the  neighbors  in  the  file
       'neighbors.csv':

       $      allkfn      --k=5     --reference_file=input.csv     --distances_file=distances.csv
       --neighbors_file=neighbors.csv

       The output files are organized such that row i and column j in the neighbors  output  file
       corresponds  to  the  index  of  the point in the reference set which is the i'th furthest
       neighbor from the point in the query set with  index  j.   Row  i  and  column  j  in  the
       distances output file corresponds to the distance between those two points.

OPTIONS

       --distances_file (-d) [string] File to output distances into. Default value ’'.

       --help (-h)
              Default help info.

       --info [string]
              Get  help  on  a  specific module or option.  Default value ''.  --input_model_file
              (-m) [string] File containing pre-trained kFN model. Default value ''.

       --k (-k) [int]
              Number of furthest neighbors to find. Default value 0.

       --leaf_size (-l) [int]
              Leaf size for tree building. Default value 20.

       --naive (-N)
              If true, O(n^2) naive mode is used for computation.  --neighbors_file (-n) [string]
              File to output neighbors into. Default value ’'.  --output_model_file (-M) [string]
              If specified, the kFN model will be saved to the given file. Default value ''.

       --query_file (-q) [string]
              File containing query points (optional).  Default value ''.

       --random_basis (-R)
              Before  tree-building,  project  the  data  onto   a   random   orthogonal   basis.
              --reference_file (-r) [string] File containing the reference dataset. Default value
              ''.

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

       --single_mode (-s)
              If true, single-tree search is used (as opposed to dual-tree search).

       --tree_type (-t) [string]
              Type of tree to use: 'kd', 'cover', 'r', ’r-star', 'ball'. Default value 'kd'.

       --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.

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_allkfn(1)