de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction

Class SimplifiedHierarchyExtraction

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction.SimplifiedHierarchyExtraction

All Implemented Interfaces:

Algorithm, ClusteringAlgorithm<Clustering<DendrogramModel>>

@Reference(authors="R. J. G. B. Campello, D. Moulavi, and J. Sander",
           title="Density-Based Clustering Based on Hierarchical Density Estimates",
           booktitle="Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD",
           url="http://dx.doi.org/10.1007/978-3-642-37456-2_14")
public class SimplifiedHierarchyExtraction
extends Object
implements ClusteringAlgorithm<Clustering<DendrogramModel>>

Extraction of simplified cluster hierarchies, as proposed in HDBSCAN. In contrast to the authors top-down approach, we use a bottom-up approach based on the more efficient pointer representation introduced in SLINK. Reference:

R. J. G. B. Campello, D. Moulavi, and J. Sander
Density-Based Clustering Based on Hierarchical Density Estimates
Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	SimplifiedHierarchyExtraction.Parameterizer Parameterization class.
protected static class	SimplifiedHierarchyExtraction.TempCluster Temporary cluster.

Field Summary

Fields

Modifier and Type	Field and Description
private HierarchicalClusteringAlgorithm	algorithm Clustering algorithm to run to obtain the hierarchy.
private static Logging	LOG Class logger.
private int	minClSize Minimum cluster size.

Constructor Summary

Constructors

Constructor and Description
SimplifiedHierarchyExtraction(HierarchicalClusteringAlgorithm algorithm, int minClSize) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
private void	addSingleton(SimplifiedHierarchyExtraction.TempCluster clus, DBIDRef id, double dist, boolean asCluster) Add a singleton object, as point or cluster.
Clustering<DendrogramModel>	extractClusters(DBIDs ids, DBIDDataStore pi, DoubleDataStore lambda, DoubleDataStore coredist) Extract all clusters from the pi-lambda-representation.
TypeInformation[]	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
private Cluster<DendrogramModel>	makeSingletonCluster(DBIDRef lead, double depth) Make the cluster for the given object
Clustering<DendrogramModel>	run(Database database) Runs the algorithm.

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

Class logger.

minClSize

private int minClSize

Minimum cluster size.

algorithm

private HierarchicalClusteringAlgorithm algorithm

Clustering algorithm to run to obtain the hierarchy.

Constructor Detail

SimplifiedHierarchyExtraction

public SimplifiedHierarchyExtraction(HierarchicalClusteringAlgorithm algorithm,
                             int minClSize)

Constructor.

Parameters:

algorithm - Algorithm to run

minClSize - Minimum cluster size

Method Detail

run

public Clustering<DendrogramModel> run(Database database)

Description copied from interface: Algorithm

Runs the algorithm.

Specified by:

run in interface Algorithm

Specified by:

run in interface ClusteringAlgorithm<Clustering<DendrogramModel>>

Parameters:

database - the database to run the algorithm on

Returns:

the Result computed by this algorithm

extractClusters

public Clustering<DendrogramModel> extractClusters(DBIDs ids,
                                          DBIDDataStore pi,
                                          DoubleDataStore lambda,
                                          DoubleDataStore coredist)

Extract all clusters from the pi-lambda-representation.

Parameters:

ids - Object ids to process

pi - Pi store

lambda - Lambda store

coredist - Core distances

Returns:

Hierarchical clustering

addSingleton

private void addSingleton(SimplifiedHierarchyExtraction.TempCluster clus,
                DBIDRef id,
                double dist,
                boolean asCluster)

Add a singleton object, as point or cluster.

Parameters:

clus - Current cluster.

id - Object to add

dist - Distance

asCluster - Add as cluster (or only as id)

makeSingletonCluster

private Cluster<DendrogramModel> makeSingletonCluster(DBIDRef lead,
                                            double depth)

Make the cluster for the given object

Parameters:

lead - Leading object

depth - Linkage depth

Returns:

Cluster

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