org.aksw.limes.core.evaluation.qualititativeMeasures

Class Precision

java.lang.Object

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

org.aksw.limes.core.evaluation.qualititativeMeasures.Precision

All Implemented Interfaces:

IQualitativeMeasure

public class Precision
extends APRF
implements IQualitativeMeasure

It can be defined as the ratio of the retrieved correct results relative to the total number of the retrieved results,i.e. Tp/(Tp+Fp).

Since:

1.0

Version:

1.0

Author:

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

Constructor Summary

Constructors

Constructor and Description
Precision()

Method Summary

Modifier and Type	Method and Description
double	calculate(AMapping predictions, GoldStandard goldStandard) The method calculates the precision 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

Precision

public Precision()

Method Detail

calculate

public double calculate(AMapping predictions,
                        GoldStandard goldStandard)

The method calculates the precision 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 precision