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

Class SimplifiedHierarchyExtractionEvaluator

java.lang.Object

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

All Implemented Interfaces:

Evaluator, ResultProcessor

public class SimplifiedHierarchyExtractionEvaluator
extends Object
implements Evaluator

Extract clusters from a hierarchical clustering, during the evaluation phase. Usually, it is more elegant to use SimplifiedHierarchyExtraction as primary algorithm. But in order to extract multiple partitionings from the same clustering, this can be useful.

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	SimplifiedHierarchyExtractionEvaluator.Parameterizer Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private SimplifiedHierarchyExtraction	inner Class to perform the cluster extraction.

Constructor Summary

Constructors

Constructor and Description
SimplifiedHierarchyExtractionEvaluator(SimplifiedHierarchyExtraction inner) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
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

inner

private SimplifiedHierarchyExtraction inner

Class to perform the cluster extraction.

Constructor Detail

SimplifiedHierarchyExtractionEvaluator

public SimplifiedHierarchyExtractionEvaluator(SimplifiedHierarchyExtraction inner)

Constructor.

Parameters:

inner - Inner algorithm instance.

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.