Class DBSCANClusterer<T extends Clusterable<T>>
- java.lang.Object
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- org.apache.commons.math3.stat.clustering.DBSCANClusterer<T>
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- 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), useDBSCANClusterer
insteadDBSCAN (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 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:
- 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 returnnull
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Constructor Summary
Constructors Constructor Description DBSCANClusterer(double eps, int minPts)
Deprecated.Creates a new instance of a DBSCANClusterer.
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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.
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Constructor Detail
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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 consideredminPts
- minimum number of points needed for a cluster- Throws:
NotPositiveException
- ifeps < 0.0
orminPts < 0
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Method Detail
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getEps
public double getEps()
Deprecated.Returns the maximum radius of the neighborhood to be considered.- Returns:
- maximum radius of the neighborhood
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getMinPts
public int getMinPts()
Deprecated.Returns the minimum number of points needed for a cluster.- Returns:
- minimum number of points needed for a cluster
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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 returnnull
.- Parameters:
points
- the points to cluster- Returns:
- the list of clusters
- Throws:
NullArgumentException
- if the data points are null
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