1mlpack_dbscan(1)                 User Commands                mlpack_dbscan(1)
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NAME

6       mlpack_dbscan - dbscan clustering
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SYNOPSIS

9        mlpack_dbscan -i string [-e double] [-m int] [-N bool] [-S bool] [-t string] [-V bool] [-a string] [-C string] [-h -v]
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DESCRIPTION

12       This  program  implements  the  DBSCAN  algorithm  for clustering using
13       accelerated tree-based range search. The type of tree that is used  may
14       be parameterized, or brute-force range search may also be used.
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16       The   input   dataset  to  be  clustered  may  be  specified  with  the
17       '--input_file (-i)' parameter; the radius of each range search  may  be
18       specified  with the ’--epsilon (-e)' parameters, and the minimum number
19       of points in a cluster may be  specified  with  the  '--min_size  (-m)'
20       parameter.
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22       The '--assignments_file (-a)' and '--centroids_file (-C)' output param‐
23       eters may be used to save the  output  of  the  clustering.  '--assign‐
24       ments_file  (-a)'  contains  the cluster assignments of each point, and
25       '--centroids_file (-C)' contains the centroids of each cluster.
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27       The range search may be controlled with the '--tree_type (-t)', '--sin‐
28       gle_mode  (-S)',  and '--naive (-N)' parameters. '--tree_type (-t)' can
29       control the type of tree used for range search; this can take a variety
30       of  values:  'kd',  'r', ’r-star', 'x', 'hilbert-r', 'r-plus', 'r-plus-
31       plus', 'cover', 'ball'. The ’--single_mode (-S)' parameter  will  force
32       single-tree  search  (as  opposed to the default dual-tree search), and
33       ''--naive (-N)' will force brute-force range search.
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35       An example usage to run DBSCAN on the dataset  in  'input.csv'  with  a
36       radius of 0.5 and a minimum cluster size of 5 is given below:
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38       $ dbscan --input_file input.csv --epsilon 0.5 --min_size 5
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REQUIRED INPUT OPTIONS

41       --input_file (-i) [string]
42              Input dataset to cluster.
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OPTIONAL INPUT OPTIONS

45       --epsilon (-e) [double]
46              Radius of each range search. Default value 1.
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48       --help (-h) [bool]
49              Default help info.
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51       --info [string]
52              Get help on a specific module or option.  Default value ''.
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54       --min_size (-m) [int]
55              Minimum number of points for a cluster. Default value 5.
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57       --naive (-N) [bool]
58              If set, brute-force range search (not tree-based) will be used.
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60       --single_mode (-S) [bool]
61              If set, single-tree range search (not dual-tree) will be used.
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63       --tree_type (-t) [string]
64              If  using  single-tree  or dual-tree search, the type of tree to
65              use ('kd', 'r', 'r-star', 'x', 'hilbert-r',  'r-plus',  'r-plus-
66              plus', 'cover', 'ball'). Default value 'kd'.
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68       --verbose (-v) [bool]
69              Display  informational  messages and the full list of parameters
70              and timers at the end of execution.
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72       --version (-V) [bool]
73              Display the version of mlpack.
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OPTIONAL OUTPUT OPTIONS

76       --assignments_file (-a) [string]
77              Output matrix for assignments of each point.  Default value ''.
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79       --centroids_file (-C) [string]
80              Matrix to save output centroids to. Default value ''.
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ADDITIONAL INFORMATION

83       For further information, including relevant papers, citations, and the‐
84       ory,  consult  the  documentation  found  at  http://www.mlpack.org  or
85       included with your distribution of mlpack.
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89mlpack-3.0.4                   21 February 2019               mlpack_dbscan(1)
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