T - type of the points to clusterpublic class DBSCANClusterer<T extends Clusterable> extends Clusterer<T>
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 pi, with i = 1 .. n and p1 = p and pn = q, such that each pair <pi, pi+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:
| Constructor and Description | 
|---|
| DBSCANClusterer(double eps,
               int minPts)Creates a new instance of a DBSCANClusterer. | 
| DBSCANClusterer(double eps,
               int minPts,
               DistanceMeasure measure)Creates a new instance of a DBSCANClusterer. | 
| Modifier and Type | Method and Description | 
|---|---|
| List<Cluster<T>> | cluster(Collection<T> points)Performs DBSCAN cluster analysis. | 
| double | getEps()Returns the maximum radius of the neighborhood to be considered. | 
| int | getMinPts()Returns the minimum number of points needed for a cluster. | 
distance, getDistanceMeasurepublic DBSCANClusterer(double eps,
               int minPts)
                throws NotPositiveException
The euclidean distance will be used as default distance measure.
eps - maximum radius of the neighborhood to be consideredminPts - minimum number of points needed for a clusterNotPositiveException - if eps < 0.0 or minPts < 0public DBSCANClusterer(double eps,
               int minPts,
               DistanceMeasure measure)
                throws NotPositiveException
eps - maximum radius of the neighborhood to be consideredminPts - minimum number of points needed for a clustermeasure - the distance measure to useNotPositiveException - if eps < 0.0 or minPts < 0public double getEps()
public int getMinPts()
public List<Cluster<T>> cluster(Collection<T> points) throws NullArgumentException
cluster in class Clusterer<T extends Clusterable>points - the points to clusterNullArgumentException - if the data points are nullCopyright © 2003–2016 The Apache Software Foundation. All rights reserved.