DBSCANClusterer (Apache Commons Math 3.6.1 API)

java.lang.Object
- org.apache.commons.math3.stat.clustering.DBSCANClusterer<T>

Type Parameters:

T - type of the points to cluster
```
@Deprecated
public class DBSCANClusterer<T extends Clusterable<T>>
extends java.lang.Object
```
Deprecated.
As of 3.2 (to be removed in 4.0), use DBSCANClusterer instead
DBSCAN (density-based spatial clustering of applications with noise) algorithm.
The DBSCAN algorithm forms clusters based on the idea of density connectivity, i.e. a point p is density connected to another point q, if there exists a chain of points p_i, with i = 1 .. n and p₁ = p and p_n = q, such that each pair <p_i, p_i+1> is directly density-reachable. A point q is directly density-reachable from point p if it is in the ε-neighborhood of this point.
Any point that is not density-reachable from a formed cluster is treated as noise, and will thus not be present in the result.
The algorithm requires two parameters:
- eps: the distance that defines the ε-neighborhood of a point
- minPoints: the minimum number of density-connected points required to form a cluster
Note: as DBSCAN is not a centroid-based clustering algorithm, the resulting Cluster objects will have no defined center, i.e. Cluster.getCenter() will return null.
Since:

3.1

See Also:

DBSCAN (wikipedia), A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise

Constructor Summary

Constructors
Constructor Description

DBSCANClusterer(double eps, int minPts)
Deprecated.

Creates a new instance of a DBSCANClusterer.

Method Summary

All Methods Instance Methods Concrete Methods Deprecated Methods
Modifier and Type	Method	Description
`java.util.List<Cluster<T>>`	`cluster(java.util.Collection<T> points)`	Deprecated. Performs DBSCAN cluster analysis.
`double`	`getEps()`	Deprecated. Returns the maximum radius of the neighborhood to be considered.
`int`	`getMinPts()`	Deprecated. Returns the minimum number of points needed for a cluster.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - DBSCANClusterer
```
public DBSCANClusterer(double eps,
                       int minPts)
                throws NotPositiveException
```
    Deprecated.
    
    Creates a new instance of a DBSCANClusterer.
    
    Parameters:
    
    eps - maximum radius of the neighborhood to be considered
    
    minPts - minimum number of points needed for a cluster
    
    Throws:
    
    NotPositiveException - if eps < 0.0 or minPts < 0
- Method Detail
  - getEps
```
public double getEps()
```
    Deprecated.
    
    Returns the maximum radius of the neighborhood to be considered.
    
    Returns:
    
    maximum radius of the neighborhood
  - getMinPts
```
public int getMinPts()
```
    Deprecated.
    
    Returns the minimum number of points needed for a cluster.
    
    Returns:
    
    minimum number of points needed for a cluster
  - cluster
```
public java.util.List<Cluster<T>> cluster(java.util.Collection<T> points)
                                   throws NullArgumentException
```
    Deprecated.
    
    Performs DBSCAN cluster analysis.
    Note: as DBSCAN is not a centroid-based clustering algorithm, the resulting Cluster objects will have no defined center, i.e. Cluster.getCenter() will return null.
    
    Parameters:
    
    points - the points to cluster
    
    Returns:
    
    the list of clusters
    
    Throws:
    
    NullArgumentException - if the data points are null