QualityMuellerMetric (ProCAKE Framework 4.0.0 API)

java.lang.Object
- de.uni_trier.wi2.procake.utils.eval.metrics.k.KEvalMetric
- - de.uni_trier.wi2.procake.utils.eval.metrics.k.QualityMuellerMetric

All Implemented Interfaces:

EvalMetric
```
public class QualityMuellerMetric
extends KEvalMetric
```
Implementation of the quality metric according to Bergmann and Müller.

Author:

Maximilian Hoffmann

Constructor Summary

Constructors
Constructor Description

QualityMuellerMetric()

QualityMuellerMetric(int k)

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`double`	`computeEvalKMetric(SimpleSimilarityResult groundTruthResult, SimpleSimilarityResult predictedResult, Integer k)`	Computes a ranking metric for the top-k cases of the ranking results.
`String`	`getMetricName()`	Returns a name for the metric to be identified in any string representations.

Methods inherited from class de.uni_trier.wi2.procake.utils.eval.metrics.k.KEvalMetric
computeEvalMetric, getK, setK

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - QualityMuellerMetric
```
public QualityMuellerMetric()
```
  - QualityMuellerMetric
```
public QualityMuellerMetric(int k)
```
- Method Detail
  - getMetricName
```
public String getMetricName()
```
    Description copied from interface: EvalMetric
    
    Returns a name for the metric to be identified in any string representations.
    
    Specified by:
    
    getMetricName in interface EvalMetric
    
    Overrides:
    
    getMetricName in class KEvalMetric
    
    Returns:
    
    the name of the metric
  - computeEvalKMetric
```
public double computeEvalKMetric(SimpleSimilarityResult groundTruthResult,
                                 SimpleSimilarityResult predictedResult,
                                 Integer k)
```
    Description copied from class: KEvalMetric
    
    Computes a ranking metric for the top-k cases of the ranking results.
    
    Specified by:
    
    computeEvalKMetric in class KEvalMetric
    
    Parameters:
    
    groundTruthResult - the ground-truth ranking
    
    predictedResult - the predicted ranking results to analyze
    
    k - the number of top cases to look at
    
    Returns:
    
    a score for the ranking according to this metric