---
name: "mlpack_dbscan"
section: "1"
platform: "linux"
package: "mlpack-bin"
version: "4.6.0-1"
release: "Debian 13 (Trixie)"
platforms: ["linux"]
url: "https://new.carta.tech/mlpack_dbscan"
---

# mlpack\_dbscan(1)

dbscan clustering

## NAME

**mlpack\_dbscan** - dbscan clustering

## SYNOPSIS

```
 mlpack_dbscan -i unknown [-e double] [-m int] [-N bool] [-s string] [-S bool] [-t string] [-V bool] [-a unknown] [-C unknown] [-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** (**-i**)' parameter; the radius of each range search may be specified with the ’**--epsilon** (**-e**)' parameters, and the minimum number of points in a cluster may be specified with the '**--min\_size** (**-m**)' parameter.

The '**--assignments\_file** (**-a**)' and '**--centroids\_file** (**-C**)' output parameters may be used to save the output of the clustering. '**--assignments\_file** (**-a**)' contains the cluster assignments of each point, and '**--centroids\_file** (**-C**)' contains the centroids of each cluster.

The range search may be controlled with the '**--tree\_type** (**-t**)', '**--single\_mode** (**-S**)', and '**--naive** (**-N**)' parameters. '**--tree\_type** (**-t**)' 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** (**-S**)' parameter will force single-tree search (as opposed to the default dual-tree search), and ''**--naive** (**-N**)' 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** **--input\_file** input.csv **--epsilon** 0.5 **--min\_size** 5

## REQUIRED INPUT OPTIONS

- **--input\_file (-i) \[*unknown*\]**

  Input dataset to cluster.

## OPTIONAL INPUT OPTIONS

- **--epsilon (-e) \[*double*\]**

  Radius of each range search. Default value 1.

- **--help (-h) \[*bool*\]**

  Default help info.

- **--info \[*string*\]**

  Print help on a specific option. Default value ''.

- **--min\_size (-m) \[*int*\]**

  Minimum number of points for a cluster. Default value 5.

- **--naive (-N) \[*bool*\]**

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

- **--selection\_type (-s) \[*string*\]**

  If using point selection policy, the type of selection to use ('ordered', 'random'). Default value 'ordered'.

- **--single\_mode (-S) \[*bool*\]**

  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) \[*bool*\]**

  Display informational messages and the full list of parameters and timers at the end of execution.

- **--version (-V) \[*bool*\]**

  Display the version of mlpack.

## OPTIONAL OUTPUT OPTIONS

- **--assignments\_file (-a) \[*unknown*\]**

  Output matrix for assignments of each point.

- **--centroids\_file (-C) \[*unknown*\]**

  Matrix to save output centroids to.

## 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.