Examples of statechum.analysis.learning.observers.Learner.learnMachine()

Package statechum.analysis.learning.observers

Class statechum.analysis.learning.observers.Learner

Examples of statechum.analysis.learning.observers.Learner.learnMachine()

statechum.analysis.learning.observers.Learner.learnMachine()
Learns the machine. When different learning events occur, the learner calls its listeners (which are the decorators); these listeners are given a chance to inspect the arguments, do something and pass the call further or not pass. At the bottom level, there is default processing performed by the learner itself.
For internal use only. @param topLevelDecorator the first listener in a chain of them.

        innerLearner.addObserver(PickNegativesVisualiser.this);
        Learner mainDecorator = new AutoAnswers(innerLearner);
        if (conf.labelDetails != null)
          mainDecorator = new SmtLearnerDecorator(mainDecorator,conf.labelDetails);
            if (whomToNotify != null) whomToNotify.threadStarted();
            LearnerGraph graph = mainDecorator.learnMachine(sPlus, sMinus);
            if (graph != null)
            {
              DirectedSparseGraph learnt = graph.pathroutines.getGraph();
              if(conf.config.isGenerateTextOutput())
                OutputUtil.generateTextOutput(learnt,"textOutput.txt");

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    config.setDebugMode(false);
    //l.setPairsMergedPerHypothesis(0);
    //l.setGeneralisationThreshold(1);
    //l.setCertaintyThreshold(5);
    testConfig.setLearnerIdMode(IDMode.POSITIVE_NEGATIVE);
    LearnerGraph learntStructureA = new LearnerGraph(l.learnMachine(buildSet(plus), buildSet(minus)),expected.config);
    // Now do the same with ptasets instead of real sets
    PTASequenceSet plusPTA = new PTASequenceSet();plusPTA.addAll(buildSet(plus));PTASequenceSet minusPTA = new PTASequenceSet();minusPTA.addAll(buildSet(minus));
    LearnerGraph learntStructureB = new LearnerGraph(l.learnMachine(plusPTA, minusPTA),expected.config);
    Assert.assertNull(WMethod.checkM(learntStructureA, learntStructureB));
    LearnerGraph learntMachineNoRejects = new LearnerGraph(expected.config);

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    //l.setCertaintyThreshold(5);
    testConfig.setLearnerIdMode(IDMode.POSITIVE_NEGATIVE);
    LearnerGraph learntStructureA = new LearnerGraph(l.learnMachine(buildSet(plus), buildSet(minus)),expected.config);
    // Now do the same with ptasets instead of real sets
    PTASequenceSet plusPTA = new PTASequenceSet();plusPTA.addAll(buildSet(plus));PTASequenceSet minusPTA = new PTASequenceSet();minusPTA.addAll(buildSet(minus));
    LearnerGraph learntStructureB = new LearnerGraph(l.learnMachine(plusPTA, minusPTA),expected.config);
    Assert.assertNull(WMethod.checkM(learntStructureA, learntStructureB));
    LearnerGraph learntMachineNoRejects = new LearnerGraph(expected.config);
    AbstractPathRoutines.removeRejectStates(learntStructureA,learntMachineNoRejects);
    Assert.assertNull(WMethod.checkM(learntMachineNoRejects, expected));
  }

View Full Code Here

        innerLearner.addObserver(PickNegativesVisualiser.this);
        Learner mainDecorator = new AutoAnswers(innerLearner);
        if (conf.labelDetails != null)
          mainDecorator = new SmtLearnerDecorator(mainDecorator,conf.labelDetails);
            if (whomToNotify != null) whomToNotify.threadStarted();
            DirectedSparseGraph learnt = mainDecorator.learnMachine(sPlus, sMinus).pathroutines.getGraph();
            if(conf.config.isGenerateTextOutput())
              OutputUtil.generateTextOutput(learnt);
            if(conf.config.isGenerateDotOutput())
              OutputUtil.generateDotOutput(learnt);

View Full Code Here

    config.setDebugMode(false);
    //l.setPairsMergedPerHypothesis(0);
    //l.setGeneralisationThreshold(1);
    //l.setCertaintyThreshold(5);
    testConfig.setLearnerIdMode(IDMode.POSITIVE_NEGATIVE);
    LearnerGraph learntStructureA = new LearnerGraph(l.learnMachine(buildSet(plus), buildSet(minus)),expected.config);


    // Now do the same with ptasets instead of real sets
    PTASequenceSet plusPTA = new PTASequenceSet();plusPTA.addAll(buildSet(plus));PTASequenceSet minusPTA = new PTASequenceSet();minusPTA.addAll(buildSet(minus));
    LearnerGraph learntStructureB = new LearnerGraph(l.learnMachine(plusPTA, minusPTA),expected.config);
    //Visualiser.updateFrame(learntStructureA, expected);

View Full Code Here

    testConfig.setLearnerIdMode(IDMode.POSITIVE_NEGATIVE);
    LearnerGraph learntStructureA = new LearnerGraph(l.learnMachine(buildSet(plus), buildSet(minus)),expected.config);


    // Now do the same with ptasets instead of real sets
    PTASequenceSet plusPTA = new PTASequenceSet();plusPTA.addAll(buildSet(plus));PTASequenceSet minusPTA = new PTASequenceSet();minusPTA.addAll(buildSet(minus));
    LearnerGraph learntStructureB = new LearnerGraph(l.learnMachine(plusPTA, minusPTA),expected.config);
    //Visualiser.updateFrame(learntStructureA, expected);
    Assert.assertNull(WMethod.checkM(learntStructureA, learntStructureB));
    LearnerGraph learntMachineNoRejects = new LearnerGraph(expected.config);
    AbstractPathRoutines.removeRejectStates(learntStructureA,learntMachineNoRejects);
    Assert.assertNull(WMethod.checkM(learntMachineNoRejects, expected));

View Full Code Here

                    mainDecorator = new SmtLearnerDecorator(mainDecorator, conf.labelDetails);
                }
                if (whomToNotify != null) {
                    whomToNotify.threadStarted();
                }
                LearnerGraph graph = mainDecorator.learnMachine(sPlus, sMinus);
                if (graph != null) {
                    DirectedSparseGraph learnt = graph.pathroutines.getGraph();
                    if (conf.config.isGenerateTextOutput()) {
                        OutputUtil.generateTextOutput(learnt, "textOutput.txt");
                    }

View Full Code Here

        innerLearner.addObserver(PickNegativesVisualiser.this);
        Learner mainDecorator = new AutoAnswers(innerLearner);
        if (conf.labelDetails != null)
          mainDecorator = new SmtLearnerDecorator(mainDecorator,conf.labelDetails);
            if (whomToNotify != null) whomToNotify.threadStarted();
            LearnerGraph graph = mainDecorator.learnMachine(sPlus, sMinus);
            if (graph != null)
            {
              DirectedSparseGraph learnt = graph.pathroutines.getGraph();
              if(conf.config.isGenerateTextOutput())
                OutputUtil.generateTextOutput(learnt,"textOutput.txt");

View Full Code Here

    config.setDebugMode(false);
    //l.setPairsMergedPerHypothesis(0);
    //l.setGeneralisationThreshold(1);
    //l.setCertaintyThreshold(5);
    testConfig.setLearnerIdMode(IDMode.POSITIVE_NEGATIVE);
    LearnerGraph learntStructureA = new LearnerGraph(l.learnMachine(buildSet(plus), buildSet(minus)),expected.config);
    // Now do the same with ptasets instead of real sets
    PTASequenceSet plusPTA = new PTASequenceSet();plusPTA.addAll(buildSet(plus));PTASequenceSet minusPTA = new PTASequenceSet();minusPTA.addAll(buildSet(minus));
    LearnerGraph learntStructureB = new LearnerGraph(l.learnMachine(plusPTA, minusPTA),expected.config);
    Assert.assertNull(WMethod.checkM(learntStructureA, learntStructureB));
    LearnerGraph learntMachineNoRejects = new LearnerGraph(expected.config);

View Full Code Here

    //l.setCertaintyThreshold(5);
    testConfig.setLearnerIdMode(IDMode.POSITIVE_NEGATIVE);
    LearnerGraph learntStructureA = new LearnerGraph(l.learnMachine(buildSet(plus), buildSet(minus)),expected.config);
    // Now do the same with ptasets instead of real sets
    PTASequenceSet plusPTA = new PTASequenceSet();plusPTA.addAll(buildSet(plus));PTASequenceSet minusPTA = new PTASequenceSet();minusPTA.addAll(buildSet(minus));
    LearnerGraph learntStructureB = new LearnerGraph(l.learnMachine(plusPTA, minusPTA),expected.config);
    Assert.assertNull(WMethod.checkM(learntStructureA, learntStructureB));
    LearnerGraph learntMachineNoRejects = new LearnerGraph(expected.config);
    AbstractPathRoutines.removeRejectStates(learntStructureA,learntMachineNoRejects);
    Assert.assertNull(WMethod.checkM(learntMachineNoRejects, expected));
  }

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