NAME

       mlpack_dbscan - dbscan clustering

SYNOPSIS

        mlpack_dbscan [-h] [-v]

DESCRIPTION

       This  program  implements  the DBSCAN algorithm for clustering using accelerated tree-based range search.
       The type of tree that is used may be parameterized, or brute-force range search may also be used.

       The input dataset to be clustered may be specified with the --input_file option, the radius of each range
       search may be specified with the --epsilon option, and the minimum number of points in a cluster  may  be
       specified with the --min_size option.

       The  output  of the clustering may be saved as --assignments_file or --centroids_file; --assignments_file
       will save the cluster assignments of each point, and --centroids_file will save  the  centroids  of  each
       cluster.

       The  range  search  may  be  controlled  with the --tree_type, --single_mode, and --naive parameters. The
       --tree_type parameter can control the type of tree used for range search; this  can  take  a  variety  of
       values:   'kd',   'r',   'r-star',  ’x',  'hilbert-r',  'r-plus',  'r-plus-plus',  'cover',  'ball'.  The
       --single_mode option will force  single-tree  search  (as  opposed  to  the  default  dual-tree  search).
       --single_mode can be useful when the RAM usage of batch search is too high. The --naive option will force
       brute-force range search.

       An  example  usage  to  run DBSCAN on the dataset in input.csv with a radius of 0.5 and a minimum cluster
       size of 5 is given below:

         $ mlpack_dbscan -i input.csv -e 0.5 -m 5

REQUIRED INPUT OPTIONS

       --input_file (-i) [string]
              Input dataset to cluster.

OPTIONAL INPUT OPTIONS

       --epsilon (-e) [double]
              Radius of each range search. Default value 1.

       --help (-h)
              Default help info.

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

       --min_size (-m) [int]
              Minimum number of points for a cluster. Default value 5.

       --naive (-N)
              If set, brute-force range search (not tree-based) will be used.

       --single_mode (-S)
              If set, single-tree range search (not dual-tree) will be used.

       --tree_type (-t) [string]
              If using single-tree or dual-tree search, the type of tree  to  use  ('kd',  'r',  'r-star',  'x',
              ’hilbert-r', 'r-plus', 'r-plus-plus', 'cover', ’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.

OPTIONAL OUTPUT OPTIONS

       --assignments_file  (-a)  [string]  Output  file  for  assignments  of  each  point.   Default  value ''.
       --centroids_file (-C) [string] File to save output centroids 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_dbscan(16 November 2017)