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

Class CenterOfMassMetaClustering<C extends Clustering<?>>

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<C>

de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain.CenterOfMassMetaClustering<C>

Type Parameters:

C - Clustering result type (inherited from inner algorithm)

All Implemented Interfaces:

Algorithm, ClusteringAlgorithm<C>

Direct Known Subclasses:

CKMeans

@Reference(authors="Erich Schubert, Alexander Koos, Tobias Emrich, Andreas Z\u00fcfle, Klaus Arthur Schmid, Arthur Zimek",
           title="A Framework for Clustering Uncertain Data",
           booktitle="Proceedings of the VLDB Endowment, 8(12)",
           url="http://www.vldb.org/pvldb/vol8/p1976-schubert.pdf",
           bibkey="DBLP:journals/pvldb/SchubertKEZSZ15")
public class CenterOfMassMetaClustering<C extends Clustering<?>>
extends AbstractAlgorithm<C>
implements ClusteringAlgorithm<C>

Center-of-mass meta clustering reduces uncertain objects to their center of mass, then runs a vector-oriented clustering algorithm on this data set.

Reference:

Erich Schubert, Alexander Koos, Tobias Emrich, Andreas Züfle, Klaus Arthur Schmid, Arthur Zimek
A Framework for Clustering Uncertain Data
In Proceedings of the VLDB Endowment, 8(12), 2015.

Since:

0.7.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	CenterOfMassMetaClustering.Parameterizer<C extends Clustering<?>> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
protected ClusteringAlgorithm<C>	inner The algorithm to be wrapped and run.
private static Logging	LOG Initialize a Logger.

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

ALGORITHM_ID

Constructor Summary

Constructors

Constructor and Description
CenterOfMassMetaClustering(ClusteringAlgorithm<C> inner) Constructor, quite trivial.

Method Summary

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.
C	run(Database database, Relation<? extends UncertainObject> relation) This run method will do the wrapping.
protected C	runClusteringAlgorithm(ResultHierarchy hierarchy, Result parent, DBIDs ids, DataStore<DoubleVector> store, int dim, java.lang.String title) Run a clustering algorithm on a single instance.

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

run

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.lmu.ifi.dbs.elki.algorithm.clustering.ClusteringAlgorithm

run

Field Detail

LOG

private static final Logging LOG

Initialize a Logger.

inner

protected ClusteringAlgorithm<C extends Clustering<?>> inner

The algorithm to be wrapped and run.

Constructor Detail

CenterOfMassMetaClustering

public CenterOfMassMetaClustering(ClusteringAlgorithm<C> inner)

Constructor, quite trivial.

Parameters:

inner - Primary clustering algorithm

Method Detail

run

public C run(Database database,
             Relation<? extends UncertainObject> relation)

This run method will do the wrapping.

Its called from AbstractAlgorithm.run(Database) and performs the call to the algorithms particular run method as well as the storing and comparison of the resulting Clusterings.

Parameters:

database - Database

relation - Data relation of uncertain objects

Returns:

Clustering result

runClusteringAlgorithm

protected C runClusteringAlgorithm(ResultHierarchy hierarchy,
                                   Result parent,
                                   DBIDs ids,
                                   DataStore<DoubleVector> store,
                                   int dim,
                                   java.lang.String title)

Run a clustering algorithm on a single instance.

Parameters:

parent - Parent result to attach to

ids - Object IDs to process

store - Input data

dim - Dimensionality

title - Title of relation

Returns:

Clustering result

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<C extends Clustering<?>>

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<C extends Clustering<?>>

Returns:

the static logger