de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan

Class GeneralizedDBSCAN.Instance<T>

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan.GeneralizedDBSCAN.Instance<T>

Enclosing class:

GeneralizedDBSCAN

public class GeneralizedDBSCAN.Instance<T>
extends Object

Instance for a particular data set.

Field Summary

Fields

Modifier and Type	Field and Description
(package private) CorePredicate.Instance<T>	corepred The core object property
private static int	FIRST_CLUSTER Noise IDs
private static int	NOISE Noise IDs
(package private) NeighborPredicate.Instance<T>	npred The neighborhood predicate
private static int	UNPROCESSED Unprocessed IDs

Constructor Summary

Constructors

Constructor and Description
GeneralizedDBSCAN.Instance(NeighborPredicate.Instance<T> npred, CorePredicate.Instance<T> corepred) Full Constructor

Method Summary

Methods

Modifier and Type	Method and Description
Clustering<Model>	run() Run the actual GDBSCAN algorithm.
protected int	setbasedExpandCluster(int clusterid, WritableIntegerDataStore clusterids, T neighbors, FiniteProgress progress) Set-based expand cluster implementation.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

UNPROCESSED

private static final int UNPROCESSED

Unprocessed IDs

See Also:

Constant Field Values

NOISE

private static final int NOISE

Noise IDs

See Also:

Constant Field Values

FIRST_CLUSTER

private static final int FIRST_CLUSTER

Noise IDs

See Also:

Constant Field Values

npred

final NeighborPredicate.Instance<T> npred

The neighborhood predicate

corepred

final CorePredicate.Instance<T> corepred

The core object property

Constructor Detail

GeneralizedDBSCAN.Instance

public GeneralizedDBSCAN.Instance(NeighborPredicate.Instance<T> npred,
                          CorePredicate.Instance<T> corepred)

Full Constructor

Parameters:

npred - Neighborhood predicate

corepred - Core object predicate

Method Detail

run

public Clustering<Model> run()

Run the actual GDBSCAN algorithm.

Returns:

Clustering result

setbasedExpandCluster

protected int setbasedExpandCluster(int clusterid,
                        WritableIntegerDataStore clusterids,
                        T neighbors,
                        FiniteProgress progress)

Set-based expand cluster implementation.

Parameters:

clusterid - ID of the current cluster.

clusterids - Current object to cluster mapping.

neighbors - Neighbors acquired by initial getNeighbors call.

progress - Progress logging

Returns:

cluster size