de.lmu.ifi.dbs.elki.evaluation.clustering

Class EvaluateClustering

java.lang.Object

de.lmu.ifi.dbs.elki.evaluation.clustering.EvaluateClustering

All Implemented Interfaces:

Evaluator, ResultProcessor

@Alias(value="de.lmu.ifi.dbs.elki.evaluation.paircounting.EvaluatePairCountingFMeasure")
public class EvaluateClustering
extends Object
implements Evaluator

Evaluate a clustering result by comparing it to an existing cluster label.

Since:

0.4.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	EvaluateClustering.Parameterizer Parameterization class.
static class	EvaluateClustering.ScoreResult Result object for outlier score judgements.

Field Summary

Fields

Modifier and Type	Field and Description
private static Logging	LOG Logger for debug output.
static OptionID	NOISE_ID Parameter flag for special noise handling.
private boolean	noiseSpecialHandling Apply special handling to noise "clusters".
static OptionID	REFERENCE_ID Parameter to obtain the reference clustering.
private ClusteringAlgorithm<?>	referencealg Reference algorithm.
static OptionID	SELFPAIR_ID Parameter flag to disable self-pairing
private boolean	selfPairing Use self-pairing in pair-counting measures

Constructor Summary

Constructors

Constructor and Description
EvaluateClustering(ClusteringAlgorithm<?> referencealg, boolean noiseSpecialHandling, boolean selfPairing) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
protected void	evaluteResult(Database db, Clustering<?> c, Clustering<?> refc) Evaluate a clustering result.
private boolean	isReferenceResult(Clustering<?> t) Test if a clustering result is a valid reference result.
void	processNewResult(ResultHierarchy hier, Result newResult) Process a result.

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

Logger for debug output.

REFERENCE_ID

public static final OptionID REFERENCE_ID

Parameter to obtain the reference clustering. Defaults to a flat label clustering.

NOISE_ID

public static final OptionID NOISE_ID

Parameter flag for special noise handling.

SELFPAIR_ID

public static final OptionID SELFPAIR_ID

Parameter flag to disable self-pairing

referencealg

private ClusteringAlgorithm<?> referencealg

Reference algorithm.

noiseSpecialHandling

private boolean noiseSpecialHandling

Apply special handling to noise "clusters".

selfPairing

private boolean selfPairing

Use self-pairing in pair-counting measures

Constructor Detail

EvaluateClustering

public EvaluateClustering(ClusteringAlgorithm<?> referencealg,
                  boolean noiseSpecialHandling,
                  boolean selfPairing)

Constructor.

Parameters:

referencealg - Reference clustering

noiseSpecialHandling - Noise handling flag

selfPairing - Self-pairing flag

Method Detail

processNewResult

public void processNewResult(ResultHierarchy hier,
                    Result newResult)

Description copied from interface: ResultProcessor

Process a result.

Specified by:

processNewResult in interface ResultProcessor

Parameters:

hier - The base of the result tree.

newResult - Newly added result subtree.

evaluteResult

protected void evaluteResult(Database db,
                 Clustering<?> c,
                 Clustering<?> refc)

Evaluate a clustering result.

Parameters:

db - Database

c - Clustering

refc - Reference clustering

isReferenceResult

private boolean isReferenceResult(Clustering<?> t)

Test if a clustering result is a valid reference result.

Parameters:

t - Clustering to test.

Returns:

true if it is considered to be a reference result.