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.TH mlpack_dbscan 1 "11 January 2024" "mlpack-4.3.0" "User Commands"
.SH NAME
\fBmlpack_dbscan \fP- dbscan clustering
.SH SYNOPSIS
.nf
.fam C
 \fBmlpack_dbscan\fP \fB-i\fP \fIunknown\fP [\fB-e\fP \fIdouble\fP] [\fB-m\fP \fIint\fP] [\fB-N\fP \fIbool\fP] [\fB-s\fP \fIstring\fP] [\fB-S\fP \fIbool\fP] [\fB-t\fP \fIstring\fP] [\fB-V\fP \fIbool\fP] [\fB-a\fP \fIunknown\fP] [\fB-C\fP \fIunknown\fP] [\fB-h\fP \fB-v\fP] 
.fam T
.fi
.fam T
.fi
.SH 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.
.PP
The input dataset to be clustered may be specified with the '\fB--input_file\fP
(\fB-i\fP)' parameter; the radius of each range search may be specified with the
\(cq\fB--epsilon\fP (\fB-e\fP)' parameters, and the minimum number of points in a cluster may
be specified with the '\fB--min_size\fP (\fB-m\fP)' parameter.
.PP
The '\fB--assignments_file\fP (\fB-a\fP)' and '\fB--centroids_file\fP (\fB-C\fP)' output parameters
may be used to save the output of the clustering. '\fB--assignments_file\fP (\fB-a\fP)'
contains the cluster assignments of each point, and '\fB--centroids_file\fP (\fB-C\fP)'
contains the centroids of each cluster.
.PP
The range search may be controlled with the '\fB--tree_type\fP (\fB-t\fP)', '\fB--single_mode\fP
(\fB-S\fP)', and '\fB--naive\fP (\fB-N\fP)' parameters. '\fB--tree_type\fP (\fB-t\fP)' can control the type
of tree used for range search; this can take a variety of values: 'kd', 'r',
\(cqr-star', 'x', 'hilbert-r', 'r-plus', 'r-plus-plus', 'cover', 'ball'. The
\(cq\fB--single_mode\fP (\fB-S\fP)' parameter will force single-tree search (as opposed to
the default dual-tree search), and ''\fB--naive\fP (\fB-N\fP)' will force brute-force
range search.
.PP
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:
.PP
$ \fBmlpack_dbscan\fP \fB--input_file\fP input.csv \fB--epsilon\fP 0.5 \fB--min_size\fP 5
.RE
.PP

.SH REQUIRED INPUT OPTIONS 

.TP
.B
\fB--input_file\fP (\fB-i\fP) [\fIunknown\fP]
Input dataset to cluster.  
.SH OPTIONAL INPUT OPTIONS 

.TP
.B
\fB--epsilon\fP (\fB-e\fP) [\fIdouble\fP]
Radius of each range search. Default value 1. 
.TP
.B
\fB--help\fP (\fB-h\fP) [\fIbool\fP]
Default help info. 
.TP
.B
\fB--info\fP [\fIstring\fP]
Print help on a specific option. Default value ''. 
.TP
.B
\fB--min_size\fP (\fB-m\fP) [\fIint\fP]
Minimum number of points for a cluster. Default value 5. 
.TP
.B
\fB--naive\fP (\fB-N\fP) [\fIbool\fP]
If set, brute-force range search (not tree-based) will be used. 
.TP
.B
\fB--selection_type\fP (\fB-s\fP) [\fIstring\fP]
If using point selection policy, the type of selection to use ('ordered', 'random'). Default value 'ordered'. 
.TP
.B
\fB--single_mode\fP (\fB-S\fP) [\fIbool\fP]
If set, single-tree range search (not dual-tree) will be used. 
.TP
.B
\fB--tree_type\fP (\fB-t\fP) [\fIstring\fP]
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'. 
.TP
.B
\fB--verbose\fP (\fB-v\fP) [\fIbool\fP]
Display informational messages and the full list of parameters and timers at the end of execution. 
.TP
.B
\fB--version\fP (\fB-V\fP) [\fIbool\fP]
Display the version of mlpack.  
.SH OPTIONAL OUTPUT OPTIONS 

.TP
.B
\fB--assignments_file\fP (\fB-a\fP) [\fIunknown\fP]
Output matrix for assignments of each point. 
.TP
.B
\fB--centroids_file\fP (\fB-C\fP) [\fIunknown\fP]
Matrix to save output centroids to.
.SH 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.