Package statechum.analysis.learning.experiments.PairSelection

Examples of statechum.analysis.learning.experiments.PairSelection.WekaDataCollector$PairComparator

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    initConfiguration.config.setUseConstraints(false);// do not use if-then during learning (refer to the explanation above)
   
    System.out.println(new Date().toString()+" Graph loaded: "+initialPTA.getStateNumber()+" states, adding at most "+ initConfiguration.config.getHowManyStatesToAddFromIFTHEN()+" if-then states");
    Transform.augmentFromIfThenAutomaton(initialPTA, null, ifthenAutomata, initConfiguration.config.getHowManyStatesToAddFromIFTHEN());// we only need  to augment our PTA once (refer to the explanation above).
    System.out.println(new Date().toString()+" if-then states added, now "+initialPTA.getStateNumber()+" states");
    WekaDataCollector dataCollector = PairQualityLearner.createDataCollector(ifDepth);
    // Run the learner that will find out how to select the correct pairs.
    LearnerThatCanClassifyPairs learnerOfPairs = new PairQualityLearner.LearnerThatUpdatesWekaResults(initConfiguration,referenceGraph,dataCollector,initialPTA);
    LearnerGraph actualAutomaton = learnerOfPairs.learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());
   
    // final weka.classifiers.trees.J48 classifier = new weka.classifiers.trees.J48();
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        learnerConfig.setAskQuestions(false);
       
       final InitialConfigurationAndData initialConfigAndData = PairQualityLearner.loadInitialAndPopulateInitialConfiguration(PairQualityLearner.largePTAFileName, learnerConfig, new Transform.InternStringLabel());

    LearnerGraph referenceGraph = new LearnerGraph(initialConfigAndData.initial.graph.config);AbstractPersistence.loadGraph("resources/largePTA/outcome_correct", referenceGraph, initialConfigAndData.learnerInitConfiguration.getLabelConverter());
      WekaDataCollector dataCollector = PairQualityLearner.createDataCollector(ifDepth);
      LearnerThatCanClassifyPairs learnerOfPairs = new PairQualityLearner.LearnerThatUpdatesWekaResults(initialConfigAndData.learnerInitConfiguration,referenceGraph,dataCollector,initialConfigAndData.initial.graph);
    learnerOfPairs.learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());
   
    FileWriter wekaInstances=new FileWriter("resources/largePTA/pairsEncountered3.arff");
    wekaInstances.write(dataCollector.trainingData.toString());
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    initConfiguration.config.setUseConstraints(false);// do not use if-then during learning (refer to the explanation above)
   
    System.out.println(new Date().toString()+" Graph loaded: "+initialPTA.getStateNumber()+" states, adding at most "+ initConfiguration.config.getHowManyStatesToAddFromIFTHEN()+" if-then states");
    Transform.augmentFromIfThenAutomaton(initialPTA, null, ifthenAutomata, initConfiguration.config.getHowManyStatesToAddFromIFTHEN());// we only need  to augment our PTA once (refer to the explanation above).
    System.out.println(new Date().toString()+" if-then states added, now "+initialPTA.getStateNumber()+" states");
    WekaDataCollector dataCollector = PairQualityLearner.createDataCollector(ifDepth);
    // Run the learner that will find out how to select the correct pairs.
    LearnerThatCanClassifyPairs learnerOfPairs = new PairQualityLearner.LearnerThatUpdatesWekaResults(initConfiguration,referenceGraph,dataCollector,initialPTA);
    LearnerGraph actualAutomaton = learnerOfPairs.learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());
   
    // final weka.classifiers.trees.J48 classifier = new weka.classifiers.trees.J48();
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        learnerConfig.setAskQuestions(false);
       
       final InitialConfigurationAndData initialConfigAndData = PairQualityLearner.loadInitialAndPopulateInitialConfiguration(PairQualityLearner.largePTAFileName, learnerConfig, new Transform.InternStringLabel());

    LearnerGraph referenceGraph = new LearnerGraph(initialConfigAndData.initial.graph.config);AbstractPersistence.loadGraph("resources/largePTA/outcome_correct", referenceGraph, initialConfigAndData.learnerInitConfiguration.getLabelConverter());
      WekaDataCollector dataCollector = PairQualityLearner.createDataCollector(ifDepth);
      LearnerThatCanClassifyPairs learnerOfPairs = new PairQualityLearner.LearnerThatUpdatesWekaResults(initialConfigAndData.learnerInitConfiguration,referenceGraph,dataCollector,initialConfigAndData.initial.graph);
    learnerOfPairs.learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());
   
    FileWriter wekaInstances=new FileWriter("resources/largePTA/pairsEncountered3.arff");
    wekaInstances.write(dataCollector.trainingData.toString());
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    initConfiguration.config.setUseConstraints(false);// do not use if-then during learning (refer to the explanation above)
   
    System.out.println(new Date().toString()+" Graph loaded: "+initialPTA.getStateNumber()+" states, adding at most "+ initConfiguration.config.getHowManyStatesToAddFromIFTHEN()+" if-then states");
    Transform.augmentFromIfThenAutomaton(initialPTA, null, ifthenAutomata, initConfiguration.config.getHowManyStatesToAddFromIFTHEN());// we only need  to augment our PTA once (refer to the explanation above).
    System.out.println(new Date().toString()+" if-then states added, now "+initialPTA.getStateNumber()+" states");
    WekaDataCollector dataCollector = PairQualityLearner.createDataCollector(ifDepth);
    // Run the learner that will find out how to select the correct pairs.
    LearnerThatCanClassifyPairs learnerOfPairs = new PairQualityLearner.LearnerThatUpdatesWekaResults(initConfiguration,referenceGraph,dataCollector,initialPTA);
    LearnerGraph actualAutomaton = learnerOfPairs.learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());
   
    // final weka.classifiers.trees.J48 classifier = new weka.classifiers.trees.J48();
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        learnerConfig.setAskQuestions(false);
       
       final InitialConfigurationAndData initialConfigAndData = PairQualityLearner.loadInitialAndPopulateInitialConfiguration(PairQualityLearner.largePTAFileName, learnerConfig, new Transform.InternStringLabel());

    LearnerGraph referenceGraph = new LearnerGraph(initialConfigAndData.initial.graph.config);AbstractPersistence.loadGraph("resources/largePTA/outcome_correct", referenceGraph, initialConfigAndData.learnerInitConfiguration.getLabelConverter());
      WekaDataCollector dataCollector = PairQualityLearner.createDataCollector(ifDepth);
      LearnerThatCanClassifyPairs learnerOfPairs = new PairQualityLearner.LearnerThatUpdatesWekaResults(initialConfigAndData.learnerInitConfiguration,referenceGraph,dataCollector,initialConfigAndData.initial.graph);
    learnerOfPairs.learnMachine(new LinkedList<List<Label>>(),new LinkedList<List<Label>>());
   
    FileWriter wekaInstances=new FileWriter("resources/largePTA/pairsEncountered3.arff");
    wekaInstances.write(dataCollector.trainingData.toString());
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Related Classes of statechum.analysis.learning.experiments.PairSelection.WekaDataCollector$PairComparator

  • statechum.analysis.learning.experiments.PairSelection.PairQualityLearner.PairMeasurements
  • statechum.analysis.learning.experiments.PaperUAS
  • statechum.Configuration.ScoreMode
  • weka.core.Attribute
  • weka.core.FastVector
  • weka.core.Instance
  • weka.core.Instances
  • org.openjena.atlas.AtlasException
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