List of fMeasure() Examples

Examples of fMeasure()

statechum.analysis.learning.PrecisionRecall.ConfusionMatrix.fMeasure()
weka.classifiers.Evaluation.fMeasure()
Calculate the F-Measure with respect to a particular class. This is defined as
```
 2 * recall * precision ---------------------- recall + precision 
```
@param classIndex the index of the class to consider as "positive" @return the F-Measure

Examples of statechum.analysis.learning.PrecisionRecall.ConfusionMatrix.fMeasure()

  {
    
    final long startTime = System.nanoTime();
    ConfusionMatrix matrix = classify(sequences, from,to);
    final long duration = System.nanoTime() - startTime;
    double result = matrix.fMeasure();
    assert !Double.isNaN(result);
    return new Pair<Double,Long>(result,duration);
  }


  public static ConfusionMatrix classify(Collection<List<Label>> sequences,LearnerGraph from, LearnerGraph to)

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Examples of statechum.analysis.learning.PrecisionRecall.ConfusionMatrix.fMeasure()

    set.addAll(expected);
    set.removeAll(detected);
    fn = set.size();
    
    ConfusionMatrix conf = new ConfusionMatrix(tp, tn, fp, fn);
    return conf.fMeasure();
  }


  @SuppressWarnings("unused")
  private ExperimentResult getAverage(List<ExperimentResult> toPrint) 
  {

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Examples of statechum.analysis.learning.PrecisionRecall.ConfusionMatrix.fMeasure()

  {
    
    final long startTime = System.nanoTime();
    ConfusionMatrix matrix = classify(sequences, from,to);
    final long duration = System.nanoTime() - startTime;
    double result = matrix.fMeasure();
    assert !Double.isNaN(result);
    return new Pair<Double,Long>(result,duration);
  }


  public static ConfusionMatrix classify(Collection<List<Label>> sequences,LearnerGraph from, LearnerGraph to)

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Examples of statechum.analysis.learning.PrecisionRecall.ConfusionMatrix.fMeasure()

    set.addAll(expected);
    set.removeAll(detected);
    fn = set.size();
    
    ConfusionMatrix conf = new ConfusionMatrix(tp, tn, fp, fn);
    return conf.fMeasure();
  }


  @SuppressWarnings("unused")
  private ExperimentResult getAverage(List<ExperimentResult> toPrint) 
  {

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Examples of statechum.analysis.learning.PrecisionRecall.ConfusionMatrix.fMeasure()

    ConfusionMatrix matrix = DiffExperiments.classify(TestFSMAlgo.buildSet(new String[][]{
        new String[]{"a"}
    },mainConfiguration,converter), from, to);
    Assert.assertEquals(1.,matrix.getPrecision(),Configuration.fpAccuracy);
    Assert.assertEquals(1.,matrix.getRecall(),Configuration.fpAccuracy);
    Assert.assertEquals(1.,matrix.fMeasure(),Configuration.fpAccuracy);
    Assert.assertEquals(0.,matrix.getSpecificity(),Configuration.fpAccuracy);
    Assert.assertEquals(0.5,matrix.BCR(),Configuration.fpAccuracy);
  }


  @Test

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Examples of statechum.analysis.learning.PrecisionRecall.ConfusionMatrix.fMeasure()

    ConfusionMatrix matrix = DiffExperiments.classify(TestFSMAlgo.buildSet(new String[][]{
        new String[]{"notransition"}
    },mainConfiguration,converter), from, to);
    Assert.assertEquals(0.,matrix.getPrecision(),Configuration.fpAccuracy);
    Assert.assertEquals(0.,matrix.getRecall(),Configuration.fpAccuracy);
    Assert.assertEquals(0.,matrix.fMeasure(),Configuration.fpAccuracy);
    Assert.assertEquals(1.,matrix.getSpecificity(),Configuration.fpAccuracy);
    Assert.assertEquals(0.5,matrix.BCR(),Configuration.fpAccuracy);
  }


  @Test

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Examples of statechum.analysis.learning.PrecisionRecall.ConfusionMatrix.fMeasure()

    ConfusionMatrix matrix = DiffExperiments.classify(TestFSMAlgo.buildSet(new String[][]{
        new String[]{"c"}
    },mainConfiguration,converter), from, to);
    Assert.assertEquals(0.,matrix.getPrecision(),Configuration.fpAccuracy);
    Assert.assertEquals(0.,matrix.getRecall(),Configuration.fpAccuracy);
    Assert.assertEquals(0.,matrix.fMeasure(),Configuration.fpAccuracy);
    Assert.assertEquals(1.,matrix.getSpecificity(),Configuration.fpAccuracy);
    Assert.assertEquals(0.5,matrix.BCR(),Configuration.fpAccuracy);
  }
  
  @Test

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Examples of statechum.analysis.learning.PrecisionRecall.ConfusionMatrix.fMeasure()

    ConfusionMatrix matrix = DiffExperiments.classify(TestFSMAlgo.buildSet(new String[][]{
        new String[]{"a","a"} // FN
    },mainConfiguration,converter), from, to);
    Assert.assertEquals(0.,matrix.getPrecision(),Configuration.fpAccuracy);
    Assert.assertEquals(0.,matrix.getRecall(),Configuration.fpAccuracy);
    Assert.assertEquals(0.,matrix.fMeasure(),Configuration.fpAccuracy);
    Assert.assertEquals(0.,matrix.getSpecificity(),Configuration.fpAccuracy);
    Assert.assertEquals(0,matrix.BCR(),Configuration.fpAccuracy);
  }

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Examples of statechum.analysis.learning.PrecisionRecall.ConfusionMatrix.fMeasure()

        new String[]{"a","a"} // FN
        ,new String[]{"b"} // TP
    },mainConfiguration,converter), from, to);
    Assert.assertEquals(1.,matrix.getPrecision(),Configuration.fpAccuracy);
    Assert.assertEquals(0.5,matrix.getRecall(),Configuration.fpAccuracy);
    Assert.assertEquals(0.66666666,matrix.fMeasure(),Configuration.fpAccuracy);
    Assert.assertEquals(0.,matrix.getSpecificity(),Configuration.fpAccuracy);
    Assert.assertEquals(0.25,matrix.BCR(),Configuration.fpAccuracy);
  }


  @Test

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Examples of statechum.analysis.learning.PrecisionRecall.ConfusionMatrix.fMeasure()

        new String[]{"a","a"} // FN
        ,new String[]{"b","b"} // FP
    },mainConfiguration,converter), from, to);
    Assert.assertEquals(0.,matrix.getPrecision(),Configuration.fpAccuracy);
    Assert.assertEquals(0,matrix.getRecall(),Configuration.fpAccuracy);
    Assert.assertEquals(0.,matrix.fMeasure(),Configuration.fpAccuracy);
    Assert.assertEquals(0.,matrix.getSpecificity(),Configuration.fpAccuracy);
    Assert.assertEquals(0,matrix.BCR(),Configuration.fpAccuracy);
  }

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