PseudoPrecision (LIMES Core Library 1.8.2 API)

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

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	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.