Package elki.clustering.dbscan

Class GeneralizedDBSCAN

java.lang.Object

elki.clustering.dbscan.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="https://doi.org/10.1023/A:1009745219419",
           bibkey="DBLP:journals/datamine/SanderEKX98")
public class GeneralizedDBSCAN
extends java.lang.Object
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
Data Mining and Knowledge Discovery, 1998.

Since:

0.5.0

Author:

Erich Schubert, Arthur Zimek

Nested Class Summary

Nested Classes

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

Nested classes/interfaces inherited from interface elki.Algorithm

Algorithm.Utils

Field Summary

Fields

Modifier and Type	Field	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	Description
GeneralizedDBSCAN(NeighborPredicate<?> npred, CorePredicate<?> corepred, boolean coremodel)	Constructor for parameterized algorithm.

Method Summary

Modifier and Type	Method	Description
Clustering<Model>	autorun(Database database)	Try to auto-run the algorithm on a database by calling a method called run, with an optional Database first, and with data relations as specified by Algorithm.getInputTypeRestriction().
TypeInformation[]	getInputTypeRestriction()	Get the input type restriction used for negotiating the data query.

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

autorun

public Clustering<Model> autorun(Database database)

Description copied from interface: Algorithm

Try to auto-run the algorithm on a database by calling a method called run, with an optional Database first, and with data relations as specified by Algorithm.getInputTypeRestriction().

Specified by:

autorun in interface Algorithm

Specified by:

autorun in interface ClusteringAlgorithm<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 interface: Algorithm

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

Specified by:

getInputTypeRestriction in interface Algorithm

Returns:

Type restriction