Examples of statechum.analysis.learning.experiments.PairSelection.PairQualityLearner.ScoresForGraph

        }
        


        {// For Markov, we do not need to learn anything at all - our Markov matrix contains enough information to classify paths and hence compare it to the reference graph.
          ConfusionMatrix mat = DiffExperiments.classifyAgainstMarkov(testSet, referenceGraph, m);
          dataSample.markovLearner = new ScoresForGraph();      
          System.out.println("Markov");
          dataSample.markovLearner.differenceBCR = new DifferenceToReferenceLanguageBCR(mat);
          System.out.println(dataSample.markovLearner.differenceBCR.getValue());
        }

    }


    // Delegates to a specific estimator
    ScoresForGraph estimateDifference(LearnerGraph reference, LearnerGraph actual,Collection<List<Label>> evaluationTestSet)
    {
      ScoresForGraph outcome = new ScoresForGraph();
      outcome.differenceStructural=DifferenceToReferenceDiff.estimationOfDifferenceDiffMeasure(reference, actual, config, 1);
      outcome.differenceBCR=DifferenceToReferenceLanguageBCR.estimationOfDifference(reference, actual,evaluationTestSet);
      System.out.println("Structure= "+outcome.differenceStructural.getValue());
      System.out.println("BCR= "+outcome.differenceBCR.getValue());
      System.out.println("---------------------------------------------------");

Related Classes of statechum.analysis.learning.experiments.PairSelection.PairQualityLearner.ScoresForGraph

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