org.aksw.limes.core.evaluation.qualititativeMeasures

Class PseudoPrecision

java.lang.Object

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

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

org.aksw.limes.core.evaluation.qualititativeMeasures.PseudoPrecision

All Implemented Interfaces:

IQualitativeMeasure

Direct Known Subclasses:

PseudoRefPrecision

public class PseudoPrecision
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 (mounir@informatik.uni-leipzig.de)

Field Summary

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

symmetricPrecision

Constructor Summary

Constructors

Constructor and Description
PseudoPrecision()
PseudoPrecision(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 precision of the machine learning predictions compared to a gold standard , which is basically how well the mapping maps one single s to one single t.

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

PseudoPrecision

public PseudoPrecision()

PseudoPrecision

public PseudoPrecision(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 precision of the machine learning predictions compared to a gold standard , which is basically how well the mapping maps one single s to one single t.

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 precision.