tutorial.clustering

Class NaiveAgglomerativeHierarchicalClustering4<O>

java.lang.Object

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

de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm<O,PointerHierarchyRepresentationResult>

tutorial.clustering.NaiveAgglomerativeHierarchicalClustering4<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Algorithm, HierarchicalClusteringAlgorithm, DistanceBasedAlgorithm<O>

@Reference(authors="R. M. Cormack",
           title="A Review of Classification",
           booktitle="Journal of the Royal Statistical Society. Series A, Vol. 134, No. 3",
           url="https://doi.org/10.2307/2344237",
           bibkey="doi:10.2307/2344237")
public class NaiveAgglomerativeHierarchicalClustering4<O>
extends AbstractDistanceBasedAlgorithm<O,PointerHierarchyRepresentationResult>
implements HierarchicalClusteringAlgorithm

This tutorial will step you through implementing a well known clustering algorithm, agglomerative hierarchical clustering, in multiple steps.

This is the third step, where we add support for different linkage strategies.

This is the naive O(n³) algorithm. See SLINK for a much faster algorithm (however, only for single-linkage).

Reference (for the update formulas):

R. M. Cormack
A Review of Classification
Journal of the Royal Statistical Society. Series A, Vol. 134, No. 3

Since:

0.6.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	NaiveAgglomerativeHierarchicalClustering4.Linkage Different linkage strategies.
static class	NaiveAgglomerativeHierarchicalClustering4.Parameterizer<O> Parameterization class

Field Summary

Fields

Modifier and Type	Field and Description
(package private) NaiveAgglomerativeHierarchicalClustering4.Linkage	linkage Current linkage in use.
private static Logging	LOG Class logger

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

ALGORITHM_ID

Fields inherited from interface de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
NaiveAgglomerativeHierarchicalClustering4(DistanceFunction<? super O> distanceFunction, NaiveAgglomerativeHierarchicalClustering4.Linkage linkage) Constructor.

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.
PointerHierarchyRepresentationResult	run(Database db, Relation<O> relation) Run the algorithm
protected static int	triangleSize(int x) Compute the size of a complete x by x triangle (minus diagonal)

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

getDistanceFunction

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.hierarchical.HierarchicalClusteringAlgorithm

run

Field Detail

LOG

private static final Logging LOG

Class logger

linkage

NaiveAgglomerativeHierarchicalClustering4.Linkage linkage

Current linkage in use.

Constructor Detail

NaiveAgglomerativeHierarchicalClustering4

public NaiveAgglomerativeHierarchicalClustering4(DistanceFunction<? super O> distanceFunction,
                                                 NaiveAgglomerativeHierarchicalClustering4.Linkage linkage)

Constructor.

Parameters:

distanceFunction - Distance function to use

linkage - Linkage strategy

Method Detail

run

public PointerHierarchyRepresentationResult run(Database db,
                                                Relation<O> relation)

Run the algorithm

Parameters:

db - Database

relation - Relation

Returns:

Clustering hierarchy

triangleSize

protected static int triangleSize(int x)

Compute the size of a complete x by x triangle (minus diagonal)

Parameters:

x - Offset

Returns:

Size of complete triangle

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<PointerHierarchyRepresentationResult>

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<PointerHierarchyRepresentationResult>

Returns:

the static logger