Provided by: mlpack-bin_2.0.1-1_amd64 bug

NAME

       mlpack_range_search - range search

SYNOPSIS

        mlpack_range_search [-h] [-v] [-d string] [-m string] [-l int] [-U double] [-L double] [-N] [-n string] [-M string] [-q string] [-R] [-r string] [--seed int] [-s] [-t string] -V

DESCRIPTION

       This  program  implements range search with a Euclidean distance metric. For a given query point, a given
       range, and a given set of reference points, the program will return all  of  the  reference  points  with
       distance  to the query point in the given range. This is performed for an entire set of query points. You
       may specify a separate set of reference and query points, or only a reference set -- which is  then  used
       as  both  the  reference and query set.  The given range is taken to be inclusive (that is, points with a
       distance exactly equal to the minimum and maximum of the range are included in the results).

       For example, the following will calculate the points within the range [2, 5] of each point in 'input.csv'
       and store the distances in 'distances.csv' and the neighbors in 'neighbors.csv':

       $    range_search    --min=2    --max=5     --reference_file=input.csv     --distances_file=distances.csv
       --neighbors_file=neighbors.csv

       The  output  files  are  organized  such  that  line i corresponds to the points found for query point i.
       Because sometimes 0 points may be found in the given range, lines of the output files may be  empty.  The
       points are not ordered in any specific manner.

       Because  the  number of points returned for each query point may differ, the resultant CSV-like files may
       not be loadable by many programs. However, at this time a better way to store this non-square  result  is
       not  known. As a result, any output files will be written as CSVs in this manner, regardless of the given
       extension.

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 range search model.  Default value ''.

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

       --max (-U) [double]
              Upper bound in range (if not specified, +inf will be used. Default value 0.

       --min (-L) [double]
              Lower bound in range. Default value 0.

       --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  range
              search 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_range_search(1)