org.aksw.limes.core.evaluation.qualititativeMeasures

Class PseudoRecall

java.lang.Object

org.aksw.limes.core.evaluation.qualititativeMeasures.APRF

org.aksw.limes.core.evaluation.qualititativeMeasures.APseudoPRF

org.aksw.limes.core.evaluation.qualititativeMeasures.PseudoRecall

All Implemented Interfaces:

IQualitativeMeasure

Direct Known Subclasses:

PseudoRefRecall

public class PseudoRecall
extends APseudoPRF

Implements a quality measure for unsupervised ML algorihtms, dubbed pseudo F-Measure. Thereby, not relying on any gold standard. The basic idea is to measure the quality of the a given Mapping by calc. how close it is to an assumed 1-to-1 Mapping between source and target.

Since:

1.0

Version:

1.0

Author:

Klaus Lyko (lyko@informatik.uni-leipzig.de), Axel-C. Ngonga Ngomo (ngonga@informatik.uni-leipzig.de), mofeed hassan

Field Summary

Fields inherited from class org.aksw.limes.core.evaluation.qualititativeMeasures.APseudoPRF

symmetricPrecision

Constructor Summary

Constructors

Constructor and Description
PseudoRecall()
PseudoRecall(boolean symmetricPrecision) Use this constructor to toggle between symmetric precision (true) and the older asymmetric Pseudo-Precision (false)

Method Summary

Modifier and Type	Method and Description
double	calculate(AMapping predictions, GoldStandard goldStandard) The method calculates the pseudo recall of the machine learning predictions compared to a gold standard , which is how many of the s and t were mapped.

Methods inherited from class org.aksw.limes.core.evaluation.qualititativeMeasures.APseudoPRF

getUse1To1Mapping, isSymmetricPrecision, isUse1To1Mapping, setSymmetricPrecision, setUse1To1Mapping

Methods inherited from class org.aksw.limes.core.evaluation.qualititativeMeasures.APRF

falseNegative, trueFalsePositive, trueNegative

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

PseudoRecall

public PseudoRecall()

PseudoRecall

public PseudoRecall(boolean symmetricPrecision)

Use this constructor to toggle between symmetric precision (true) and the older asymmetric Pseudo-Precision (false)

Parameters:

symmetricPrecision - sets/resets the symmetric precision flag

Method Detail

calculate

public double calculate(AMapping predictions,
                        GoldStandard goldStandard)

The method calculates the pseudo recall of the machine learning predictions compared to a gold standard , which is how many of the s and t were mapped.

Specified by:

calculate in interface IQualitativeMeasure

Specified by:

calculate in class APseudoPRF

Parameters:

predictions - The predictions provided by a machine learning algorithm.

goldStandard - It contains the gold standard (reference mapping) combined with the source and target URIs.

Returns:

double - This returns the calculated pseudo recall.