Package statechum.analysis.learning.PrecisionRecall

Examples of statechum.analysis.learning.PrecisionRecall.ConfusionMatrix

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  public void testClassify6()
  {
    LearnerGraph from = buildLearnerGraph("A-a->A-b->B / A-c-#C","testClassify1a",mainConfiguration,converter),
    to=buildLearnerGraph("A-b->A-a->B","testClassify1b",mainConfiguration,converter);
   
    ConfusionMatrix matrix = DiffExperiments.classify(TestFSMAlgo.buildSet(new String[][]{
        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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  public void testClassify7()
  {
    LearnerGraph from = buildLearnerGraph("A-a->A-b->B / A-c-#C","testClassify1a",mainConfiguration,converter),
    to=buildLearnerGraph("A-b->A-a->B","testClassify1b",mainConfiguration,converter);
   
    ConfusionMatrix matrix = DiffExperiments.classify(TestFSMAlgo.buildSet(new String[][]{
        new String[]{"a","a"} // FN
        ,new String[]{"b","b"} // FP
        ,new String[]{"c"} // TN
    },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(0.5,matrix.getSpecificity(),Configuration.fpAccuracy);
    Assert.assertEquals(0.25,matrix.BCR(),Configuration.fpAccuracy);
  }
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  public void testClassify8()
  {
    LearnerGraph from = buildLearnerGraph("A-a->A-b->B / A-c-#C","testClassify1a",mainConfiguration,converter),
    to=buildLearnerGraph("A-b->A-a->B","testClassify1b",mainConfiguration,converter);
   
    ConfusionMatrix matrix = DiffExperiments.classify(TestFSMAlgo.buildSet(new String[][]{
        new String[] {"a"} // TP
        ,new String[] {"b"} // TP
        ,new String[]{"b","b"} // FP
        ,new String[]{"c"} // TN
    },mainConfiguration,converter), from, to);
    Assert.assertEquals(2./3.,matrix.getPrecision(),Configuration.fpAccuracy);
    Assert.assertEquals(1,matrix.getRecall(),Configuration.fpAccuracy);
    Assert.assertEquals(0.8,matrix.fMeasure(),Configuration.fpAccuracy);
    Assert.assertEquals(0.5,matrix.getSpecificity(),Configuration.fpAccuracy);
    Assert.assertEquals(0.75,matrix.BCR(),Configuration.fpAccuracy);
  }
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     * @param cpuNumber the number of processors to use. Usually set to 1 because we run as many experiments as there are CPUs and so individual experiments should not consume more computational power than we have available for them.
     */
    public static DifferenceToReferenceLanguage estimationOfDifference(LearnerGraph referenceGraph, LearnerGraph actualAutomaton, Collection<List<Label>> testSet)
    {
           LearnerGraph learntGraph = new LearnerGraph(actualAutomaton.config);AbstractPathRoutines.removeRejectStates(actualAutomaton,learntGraph);
           ConfusionMatrix mat = DiffExperiments.classify(testSet, referenceGraph, learntGraph);
      return new DifferenceToReferenceLanguage(mat);
    }
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     * @param cpuNumber the number of processors to use. Usually set to 1 because we run as many experiments as there are CPUs and so individual experiments should not consume more computational power than we have available for them.
     */
    public static DifferenceToReferenceLanguageBCR estimationOfDifference(LearnerGraph referenceGraph, LearnerGraph actualAutomaton, Collection<List<Label>> testSet)
    {
           LearnerGraph learntGraph = new LearnerGraph(actualAutomaton.config);AbstractPathRoutines.removeRejectStates(actualAutomaton,learntGraph);
           ConfusionMatrix mat = DiffExperiments.classify(testSet, referenceGraph, learntGraph);
      return new DifferenceToReferenceLanguageBCR(mat);
    }
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  {
    Configuration config = Configuration.getDefaultConfiguration();
    LearnerGraph from = new LearnerGraph(buildGraph("A-a->A-b->B / A-c-#C","testClassify1a"),config),
    to=new LearnerGraph(buildGraph("A-b->A-a->B","testClassify1b"),config);
   
    ConfusionMatrix matrix = DiffExperiments.classify(TestFSMAlgo.buildSet(new String[][]{
        new String[]{"a"}
    }), 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);
  }
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  {
    Configuration config = Configuration.getDefaultConfiguration();
    LearnerGraph from = new LearnerGraph(buildGraph("A-a->A-b->B / A-c-#C","testClassify1a"),config),
    to=new LearnerGraph(buildGraph("A-b->A-a->B","testClassify1b"),config);
   
    ConfusionMatrix matrix = DiffExperiments.classify(TestFSMAlgo.buildSet(new String[][]{
        new String[]{"notransition"}
    }), 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);
  }
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  {
    Configuration config = Configuration.getDefaultConfiguration();
    LearnerGraph from = new LearnerGraph(buildGraph("A-a->A-b->B / A-c-#C","testClassify1a"),config),
    to=new LearnerGraph(buildGraph("A-b->A-a->B","testClassify1b"),config);
   
    ConfusionMatrix matrix = DiffExperiments.classify(TestFSMAlgo.buildSet(new String[][]{
        new String[]{"c"}
    }), 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);
  }
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  {
    Configuration config = Configuration.getDefaultConfiguration();
    LearnerGraph from = new LearnerGraph(buildGraph("A-a->A-b->B / A-c-#C","testClassify1a"),config),
    to=new LearnerGraph(buildGraph("A-b->A-a->B","testClassify1b"),config);
   
    ConfusionMatrix matrix = DiffExperiments.classify(TestFSMAlgo.buildSet(new String[][]{
        new String[]{"a","a"} // FN
    }), 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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  {
    Configuration config = Configuration.getDefaultConfiguration();
    LearnerGraph from = new LearnerGraph(buildGraph("A-a->A-b->B / A-c-#C","testClassify1a"),config),
    to=new LearnerGraph(buildGraph("A-b->A-a->B","testClassify1b"),config);
   
    ConfusionMatrix matrix = DiffExperiments.classify(TestFSMAlgo.buildSet(new String[][]{
        new String[]{"a","a"} // FN
        ,new String[]{"b"} // TP
    }), 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);
  }
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Related Classes of statechum.analysis.learning.PrecisionRecall.ConfusionMatrix

  • statechum.analysis.Erlang.Synapse$StatechumProcess
  • statechum.analysis.learning.experiments.mutation.DiffExperiments
  • statechum.analysis.learning.experiments.mutation.TestDiffExperiments
  • statechum.analysis.learning.experiments.PairSelection.CVS$LearnerRunner
  • statechum.analysis.learning.experiments.PairSelection.CVS_With_Random_traces_Generation$LearnerRunner
  • statechum.analysis.learning.experiments.PairSelection.MarkovLearnerExperimentWithStatisticalAnalysis$LearnerRunner
  • statechum.analysis.learning.experiments.PairSelection.PairQualityLearner$DifferenceToReferenceFMeasure
  • statechum.analysis.learning.experiments.PairSelection.PairQualityLearner$DifferenceToReferenceLanguage
  • statechum.analysis.learning.experiments.PairSelection.PairQualityLearner$DifferenceToReferenceLanguageBCR
  • statechum.analysis.learning.experiments.PaperUAS
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