.\" Text automatically generated by txt2man
.TH mlpack_mean_shift 1 "11 January 2024" "mlpack-4.3.0" "User Commands"
.SH NAME
\fBmlpack_mean_shift \fP- mean shift clustering
.SH SYNOPSIS
.nf
.fam C
 \fBmlpack_mean_shift\fP \fB-i\fP \fIunknown\fP [\fB-f\fP \fIbool\fP] [\fB-P\fP \fIbool\fP] [\fB-l\fP \fIbool\fP] [\fB-m\fP \fIint\fP] [\fB-r\fP \fIdouble\fP] [\fB-V\fP \fIbool\fP] [\fB-C\fP \fIunknown\fP] [\fB-o\fP \fIunknown\fP] [\fB-h\fP \fB-v\fP] 
.fam T
.fi
.fam T
.fi
.SH DESCRIPTION


This program performs mean shift clustering on the given dataset, storing the
learned cluster assignments either as a column of labels in the input dataset
or separately.
.PP
The input dataset should be specified with the '\fB--input_file\fP (\fB-i\fP)' parameter,
and the radius used for search can be specified with the '\fB--radius\fP (\fB-r\fP)'
parameter. The maximum number of iterations before algorithm termination is
controlled with the '\fB--max_iterations\fP (\fB-m\fP)' parameter.
.PP
The output labels may be saved with the '\fB--output_file\fP (\fB-o\fP)' output parameter
and the centroids of each cluster may be saved with the '\fB--centroid_file\fP (\fB-C\fP)'
output parameter.
.PP
For example, to run mean shift clustering on the dataset 'data.csv' and store
the centroids to 'centroids.csv', the following command may be used: 
.PP
$ \fBmlpack_mean_shift\fP \fB--input_file\fP data.csv \fB--centroid_file\fP centroids.csv
.RE
.PP

.SH REQUIRED INPUT OPTIONS 

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

.TP
.B
\fB--force_convergence\fP (\fB-f\fP) [\fIbool\fP]
If specified, the mean shift algorithm will continue running regardless of max_iterations until the clusters converge. 
.TP
.B
\fB--help\fP (\fB-h\fP) [\fIbool\fP]
Default help info. 
.TP
.B
\fB--in_place\fP (\fB-P\fP) [\fIbool\fP]
If specified, a column containing the learned cluster assignments will be added to the input 
dataset file. In this case, \fB--output_file\fP is overridden. (Do not use with Python.) 
.TP
.B
\fB--info\fP [string]
Print help on a specific option. Default value ''. 
.TP
.B
\fB--labels_only\fP (\fB-l\fP) [\fIbool\fP]
If specified, only the output labels will be 
written to the file specified by \fB--output_file\fP. 
.TP
.B
\fB--max_iterations\fP (\fB-m\fP) [\fIint\fP]
Maximum number of iterations before mean shift terminates. Default value 1000. 
.TP
.B
\fB--radius\fP (\fB-r\fP) [\fIdouble\fP]
If the distance between two centroids is less than the given radius, one will be removed. A radius of 0 or less means an estimate will be calculated and used for the radius. Default value 0. 
.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--centroid_file\fP (\fB-C\fP) [\fIunknown\fP]
If specified, the centroids of each cluster will be written to the given matrix. 
\fB--output_file\fP (\fB-o\fP) [\fIunknown\fP] Matrix to write output labels or labeled data 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.