Precision (LIMES Core Library 1.7.9 API)

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 Description

Precision()

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	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