org.aksw.limes.core.evaluation.qualititativeMeasures

Class AUC

java.lang.Object

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

org.aksw.limes.core.evaluation.qualititativeMeasures.AUC

All Implemented Interfaces:

IQualitativeMeasure

public class AUC
extends APRF
implements IQualitativeMeasure

Quantitative measure representing the area under the curve of ROC (see here).

Version:

1.0

Author:

Mofeed Hassan (mounir@informatik.uni-leipzig.de), Tommaso Soru (tsoru@informatik.uni-leipzig.de), Klaus Lyko (lyko@informatik.uni-leizig.de)

Constructor Summary

Constructors

Constructor and Description
AUC()

Method Summary

Modifier and Type	Method and Description
double	calculate(AMapping predictions, GoldStandard goldStandard) The Abstract method to be implemented for calculating the accuracy of the machine learning predictions compared to a gold standard

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

AUC

public AUC()

Method Detail

calculate

public double calculate(AMapping predictions,
                        GoldStandard goldStandard)

Description copied from class: APRF

The Abstract method to be implemented for calculating the accuracy of the machine learning predictions compared to a gold standard

Specified by:

calculate in interface IQualitativeMeasure

Specified by:

calculate in class APRF

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 accuracy