tutorial.clustering

Class NaiveAgglomerativeHierarchicalClustering3<O>

java.lang.Object

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

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

tutorial.clustering.NaiveAgglomerativeHierarchicalClustering3<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Algorithm, 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 NaiveAgglomerativeHierarchicalClustering3<O>
extends AbstractDistanceBasedAlgorithm<O,Result>

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	NaiveAgglomerativeHierarchicalClustering3.Linkage Different linkage strategies.
static class	NaiveAgglomerativeHierarchicalClustering3.Parameterizer<O> Parameterization class

Field Summary

Fields

Modifier and Type	Field and Description
(package private) NaiveAgglomerativeHierarchicalClustering3.Linkage	linkage Current linkage in use.
private static Logging	LOG Class logger
(package private) int	numclusters Threshold, how many clusters to extract.

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
NaiveAgglomerativeHierarchicalClustering3(DistanceFunction<? super O> distanceFunction, int numclusters, NaiveAgglomerativeHierarchicalClustering3.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.
Result	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.Algorithm

run

Field Detail

LOG

private static final Logging LOG

Class logger

numclusters

int numclusters

Threshold, how many clusters to extract.

linkage

NaiveAgglomerativeHierarchicalClustering3.Linkage linkage

Current linkage in use.

Constructor Detail

NaiveAgglomerativeHierarchicalClustering3

public NaiveAgglomerativeHierarchicalClustering3(DistanceFunction<? super O> distanceFunction,
                                                 int numclusters,
                                                 NaiveAgglomerativeHierarchicalClustering3.Linkage linkage)

Constructor.

Parameters:

distanceFunction - Distance function to use

numclusters - Number of clusters

linkage - Linkage strategy

Method Detail

run

public Result 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<Result>

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<Result>

Returns:

the static logger