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

Class GeneralizedDBSCAN

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<Clustering<Model>>

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

All Implemented Interfaces:

Algorithm, ClusteringAlgorithm<Clustering<Model>>

Direct Known Subclasses:

FDBSCAN, FourC, PreDeCon

@Reference(authors="J\u00f6rg Sander, Martin Ester, Hans-Peter Kriegel, Xiaowei Xu",
           title="Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications",
           booktitle="Data Mining and Knowledge Discovery",
           url="http://dx.doi.org/10.1023/A:1009745219419")
public class GeneralizedDBSCAN
extends AbstractAlgorithm<Clustering<Model>>
implements ClusteringAlgorithm<Clustering<Model>>

Generalized DBSCAN, density-based clustering with noise. Reference:

Jörg Sander, Martin Ester, Hans-Peter Kriegel, Xiaowei Xu
Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications
In: Data Mining and Knowledge Discovery, 1998.

Author:

Erich Schubert, Arthur Zimek

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	GeneralizedDBSCAN.Instance<T> Instance for a particular data set.
static class	GeneralizedDBSCAN.Parameterizer Parameterization class

Field Summary

Fields

Modifier and Type	Field and Description
protected boolean	coremodel Track which objects are "core" objects.
protected CorePredicate	corepred The core predicate factory.
private static Logging	LOG Get a logger for this algorithm
protected NeighborPredicate	npred The neighborhood predicate factory.

Constructor Summary

Constructors

Constructor and Description
GeneralizedDBSCAN(NeighborPredicate npred, CorePredicate corepred, boolean coremodel) Constructor for parameterized algorithm.

Method Summary

Methods

Modifier and Type	Method and Description
TypeInformation[]	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
protected Logging	getLogger() Get the (STATIC) logger for this class.
Clustering<Model>	run(Database database) Runs the algorithm.

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

makeParameterDistanceFunction

Methods inherited from class java.lang.Object

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

Field Detail

LOG

private static final Logging LOG

Get a logger for this algorithm

npred

protected NeighborPredicate npred

The neighborhood predicate factory.

corepred

protected CorePredicate corepred

The core predicate factory.

coremodel

protected boolean coremodel

Track which objects are "core" objects.

Constructor Detail

GeneralizedDBSCAN

public GeneralizedDBSCAN(NeighborPredicate npred,
                 CorePredicate corepred,
                 boolean coremodel)

Constructor for parameterized algorithm.

Parameters:

npred - Neighbor predicate.

corepred - Core point predicate.

coremodel - Keep track of core points.

Method Detail

run

public Clustering<Model> run(Database database)

Description copied from interface: Algorithm

Runs the algorithm.

Specified by:

run in interface Algorithm

Specified by:

run in interface ClusteringAlgorithm<Clustering<Model>>

Overrides:

run in class AbstractAlgorithm<Clustering<Model>>

Parameters:

database - the database to run the algorithm on

Returns:

the Result computed by this algorithm

getInputTypeRestriction

public TypeInformation[] getInputTypeRestriction()

Description copied from class: AbstractAlgorithm

Get the input type restriction used for negotiating the data query.

Specified by:

getInputTypeRestriction in interface Algorithm

Specified by:

getInputTypeRestriction in class AbstractAlgorithm<Clustering<Model>>

Returns:

Type restriction

getLogger

protected Logging getLogger()

Description copied from class: AbstractAlgorithm

Get the (STATIC) logger for this class.

Specified by:

getLogger in class AbstractAlgorithm<Clustering<Model>>

Returns:

the static logger