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

Class AbstractHDBSCAN<O,R extends Result>

java.lang.Object

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

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

de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.AbstractHDBSCAN<O,R>

Type Parameters:

O - Input object type

R - Output result type

All Implemented Interfaces:

Algorithm, DistanceBasedAlgorithm<O>

Direct Known Subclasses:

HDBSCANLinearMemory, SLINKHDBSCANLinearMemory

@Title(value="HDBSCAN: Hierarchical Density-Based Spatial Clustering of Applications with Noise")
@Description(value="Density-Based Clustering Based on Hierarchical Density Estimates")
@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 abstract class AbstractHDBSCAN<O,R extends Result>
extends AbstractDistanceBasedAlgorithm<O,R>

Abstract base class for HDBSCAN variations. 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
protected static class	AbstractHDBSCAN.HDBSCANAdapter Class for processing the HDBSCAN G_mpts graph.
static class	AbstractHDBSCAN.HeapMSTCollector Class for collecting the minimum spanning tree edges into a heap.
static class	AbstractHDBSCAN.Parameterizer<O> Parameterization class

Field Summary

Fields

Modifier and Type	Field and Description
protected int	minPts MinPts parameter.

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

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
AbstractHDBSCAN(DistanceFunction<? super O> distanceFunction, int minPts) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
protected WritableDoubleDataStore	computeCoreDists(DBIDs ids, KNNQuery<O> knnQ, int minPts) Compute the core distances for all objects.
protected void	convertToPointerRepresentation(ArrayDBIDs ids, DoubleLongHeap heap, WritableDBIDDataStore pi, WritableDoubleDataStore lambda) Convert spanning tree to a pointer representation.
TypeInformation[]	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.

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

getDistanceFunction

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

getLogger, makeParameterDistanceFunction, 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

minPts

protected final int minPts

MinPts parameter.

Constructor Detail

AbstractHDBSCAN

public AbstractHDBSCAN(DistanceFunction<? super O> distanceFunction,
               int minPts)

Constructor.

Parameters:

distanceFunction - Distance function

minPts - Minimum number of points for density

Method Detail

computeCoreDists

protected WritableDoubleDataStore computeCoreDists(DBIDs ids,
                                       KNNQuery<O> knnQ,
                                       int minPts)

Compute the core distances for all objects.

Parameters:

ids - Objects

knnQ - kNN query

minPts - Minimum neighborhood size

Returns:

Data store with core distances

convertToPointerRepresentation

protected void convertToPointerRepresentation(ArrayDBIDs ids,
                                  DoubleLongHeap heap,
                                  WritableDBIDDataStore pi,
                                  WritableDoubleDataStore lambda)

Convert spanning tree to a pointer representation. Note: the heap must use the correct encoding of indexes.

Parameters:

ids - IDs indexed

heap - Heap

pi - Parent array

lambda - Distance array

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<R extends Result>

Returns:

Type restriction