Examples of Learner

aima.core.learning.framework.Learner
@author Ravi Mohan
com.digitalpebble.classification.Learner
com.sleepycat.je.rep.elections.Learner
The Learner agent. It runs in its own dedicated thread, listening for messages announcing the results of elections. The Learner in turn invokes Listeners within the process to propagate the result.
statechum.analysis.learning.Learner
statechum.analysis.learning.observers.Learner

Examples of aima.core.learning.framework.Learner


    return tree;
  }


  private ConstantDecisonTree majorityValue(DataSet ds) {
    Learner learner = new MajorityLearner();
    learner.train(ds);
    return new ConstantDecisonTree(learner.predict(ds.getExample(0)));
  }

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Examples of aima.core.learning.framework.Learner


    return tree;
  }


  private ConstantDecisonTree majorityValue(DataSet ds) {
    Learner learner = new MajorityLearner();
    learner.train(ds);
    return new ConstantDecisonTree(learner.predict(ds.getExample(0)));
  }

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Examples of com.digitalpebble.classification.Learner

    // create it
    File directory = new File("./temp");
    if(directory.exists() == false){
     new File("./temp").mkdir();
    }    
    Learner creator = Learner.getLearner("./temp",Learner.LibSVMModelCreator,true);
    creator.setParameters(parameters);
    creator.setMethod(Parameters.WeightingMethod.BOOLEAN);


    RAMTrainingCorpus subjectiveCorpus = getCorpus(fileSubj,"subjective",creator);
    RAMTrainingCorpus objectiveCorpus = getCorpus(fileObj,"objective",creator);
    subjectiveCorpus.addAll(objectiveCorpus);
    
    // filter some of the attributes out based on their LLR score
    creator.keepTopNAttributesLLR(2000);
    
    // prune terms
    // creator.pruneTermsDocFreq(2,subjectiveCorpus.size());
    
    long l0 = System.currentTimeMillis();
    creator.learn(subjectiveCorpus);
    long l1 = System.currentTimeMillis();
    System.err.println("learning done in "+(l1-l0));
  }

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Examples of com.sleepycat.je.rep.elections.Learner

            new Protocol(TimebasedProposalGenerator.getParser(),
                         MasterValue.getParser(),
                         monitorConfig.getGroupName(),
                         nameIdPair,
                         null);
        learner = new Learner(electionProtocol, serviceDispatcher);
        serviceDispatcher.register(new MonitorService(this,
                                                      serviceDispatcher));
        masterChangeListener = new MasterChangeListener();
        learner.addListener(masterChangeListener);
        learner.start();

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Examples of com.sleepycat.je.rep.elections.Learner

            new Protocol(TimebasedProposalGenerator.getParser(),
                         MasterValue.getParser(),
                         monitorConfig.getGroupName(),
                         nameIdPair,
                         null);
        learner = new Learner(electionProtocol, serviceDispatcher, nameIdPair);
        serviceDispatcher.register(new MonitorService(this, 
                                                      serviceDispatcher));
        masterChangeListener = new MasterChangeListener();
        learner.addListener(masterChangeListener);
        learner.start();

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Examples of statechum.analysis.learning.Learner

    for(String [] path:plus)
      assert AbstractOracle.USER_ACCEPTED == expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config,getLabelConverter()));
    for(String [] path:minus)
      assert AbstractOracle.USER_ACCEPTED != expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config,getLabelConverter()));
    // Visualiser.getVisualiser()
    Learner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
    {
      @Override
      public LearnerGraph MergeAndDeterminize(LearnerGraph original, StatePair pair) 
      {
        // Check that compatibility score computation gives the same response as if we did merge and computed a difference between the number of states.
        ScoreMode origScore = original.config.getLearnerScoreMode();original.config.setLearnerScoreMode(ScoreMode.COMPATIBILITY);
        long compatibilityScore = original.pairscores.computePairCompatibilityScore(pair);
        original.config.setLearnerScoreMode(origScore);
        LearnerGraph outcome = super.MergeAndDeterminize(original, pair);
        Assert.assertEquals(compatibilityScore+1,original.getStateNumber()-outcome.getStateNumber());
        return outcome;
      }


      @Override
      public Pair<Integer,String> CheckWithEndUser(
          @SuppressWarnings("unused")  LearnerGraph model,
          List<Label> question, @SuppressWarnings("unused") int valueForNoRestart,
          @SuppressWarnings("unused") List<Boolean> acceptedElements,
          @SuppressWarnings("unused") PairScore pairBeingMerged,
          @SuppressWarnings("unused")  final Object [] moreOptions)
      {
        Pair<Integer,String> oracleAnswer = new Pair<Integer,String>(expected.paths.tracePathPrefixClosed(question),null);
        return oracleAnswer;        
      }
      
    };
    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,testConfig,getLabelConverter()), buildSet(minus,testConfig,getLabelConverter())),expected.config);
    // Now do the same with ptasets instead of real sets
    PTASequenceSet plusPTA = new PTASequenceSet();plusPTA.addAll(buildSet(plus,testConfig,getLabelConverter()));PTASequenceSet minusPTA = new PTASequenceSet();minusPTA.addAll(buildSet(minus,testConfig,getLabelConverter()));
    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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Examples of statechum.analysis.learning.Learner

    for(String [] path:plus)
      assert AbstractOracle.USER_ACCEPTED == expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config,getLabelConverter()));
    for(String [] path:minus)
      assert AbstractOracle.USER_ACCEPTED != expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config,getLabelConverter()));
    // Visualiser.getVisualiser()
    Learner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
    {
      @Override
      public LearnerGraph MergeAndDeterminize(LearnerGraph original, StatePair pair) 
      {
        // Check that compatibility score computation gives the same response as if we did merge and computed a difference between the number of states.
        ScoreMode origScore = original.config.getLearnerScoreMode();original.config.setLearnerScoreMode(ScoreMode.COMPATIBILITY);
        long compatibilityScore = original.pairscores.computePairCompatibilityScore(pair);
        original.config.setLearnerScoreMode(origScore);
        LearnerGraph outcome = super.MergeAndDeterminize(original, pair);
        Assert.assertEquals(compatibilityScore+1,original.getStateNumber()-outcome.getStateNumber());
        return outcome;
      }


      @Override
      public Pair<Integer,String> CheckWithEndUser(
          @SuppressWarnings("unused")  LearnerGraph model,
          List<Label> question, @SuppressWarnings("unused") int valueForNoRestart,
          @SuppressWarnings("unused") List<Boolean> acceptedElements,
          @SuppressWarnings("unused") PairScore pairBeingMerged,
          @SuppressWarnings("unused")  final Object [] moreOptions)
      {
        Pair<Integer,String> oracleAnswer = new Pair<Integer,String>(expected.paths.tracePathPrefixClosed(question),null);
        return oracleAnswer;        
      }
      
    };
    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,testConfig,getLabelConverter()), buildSet(minus,testConfig,getLabelConverter())),expected.config);
    // Now do the same with ptasets instead of real sets
    PTASequenceSet plusPTA = new PTASequenceSet();plusPTA.addAll(buildSet(plus,testConfig,getLabelConverter()));PTASequenceSet minusPTA = new PTASequenceSet();minusPTA.addAll(buildSet(minus,testConfig,getLabelConverter()));
    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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Examples of statechum.analysis.learning.Learner

    for(String [] path:plus)
      assert AbstractOracle.USER_ACCEPTED == expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config,getLabelConverter()));
    for(String [] path:minus)
      assert AbstractOracle.USER_ACCEPTED != expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config,getLabelConverter()));
    // Visualiser.getVisualiser()
    Learner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
    {
      @Override
      public LearnerGraph MergeAndDeterminize(LearnerGraph original, StatePair pair) 
      {
        // Check that compatibility score computation gives the same response as if we did merge and computed a difference between the number of states.
        ScoreMode origScore = original.config.getLearnerScoreMode();original.config.setLearnerScoreMode(ScoreMode.COMPATIBILITY);
        long compatibilityScore = original.pairscores.computePairCompatibilityScore(pair);
        original.config.setLearnerScoreMode(origScore);
        LearnerGraph outcome = super.MergeAndDeterminize(original, pair);
        Assert.assertEquals(compatibilityScore+1,original.getStateNumber()-outcome.getStateNumber());
        return outcome;
      }


      @Override
      public Pair<Integer,String> CheckWithEndUser(
          @SuppressWarnings("unused")  LearnerGraph model,
          List<Label> question, @SuppressWarnings("unused") int valueForNoRestart,
          @SuppressWarnings("unused") List<Boolean> acceptedElements,
          @SuppressWarnings("unused") PairScore pairBeingMerged,
          @SuppressWarnings("unused")  final Object [] moreOptions)
      {
        Pair<Integer,String> oracleAnswer = new Pair<Integer,String>(expected.paths.tracePathPrefixClosed(question),null);
        return oracleAnswer;        
      }
      
    };
    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,testConfig,getLabelConverter()), buildSet(minus,testConfig,getLabelConverter())),expected.config);
    // Now do the same with ptasets instead of real sets
    PTASequenceSet plusPTA = new PTASequenceSet();plusPTA.addAll(buildSet(plus,testConfig,getLabelConverter()));PTASequenceSet minusPTA = new PTASequenceSet();minusPTA.addAll(buildSet(minus,testConfig,getLabelConverter()));
    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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Examples of statechum.analysis.learning.Learner


    public static void main(String[] args) {
        QSMTool tool = new QSMTool();
        tool.loadConfig(args[0]);
        if (tool.showLTL) {
            Learner l = new RPNIUniversalLearner(null, tool.learnerInitConfiguration);
            LTL_to_ba ba = new LTL_to_ba(tool.learnerInitConfiguration.config);
            if (ba.ltlToBA(tool.learnerInitConfiguration.ifthenSequences, l.init(tool.sPlus, tool.sMinus), true,
                    GlobalConfiguration.getConfiguration().getProperty(GlobalConfiguration.G_PROPERTIES.LTL2BA))) {
                try {
                    LearnerGraph graph = Transform.ltlToIfThenAutomaton(ba.getLTLgraph().pathroutines.buildDeterministicGraph());
                    DirectedSparseGraph gr = graph.pathroutines.getGraph();
                    PathRoutines.convertPairAssociationsToTransitions(gr, graph, tool.learnerInitConfiguration.config);

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Examples of statechum.analysis.learning.Learner

    for(String [] path:plus)
      assert AbstractOracle.USER_ACCEPTED == expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config,getLabelConverter()));
    for(String [] path:minus)
      assert AbstractOracle.USER_ACCEPTED != expected.paths.tracePathPrefixClosed(AbstractLearnerGraph.buildList(Arrays.asList(path),config,getLabelConverter()));
    // Visualiser.getVisualiser()
    Learner l = new RPNIUniversalLearner(null,new LearnerEvaluationConfiguration(null,null,testConfig,null,null))
    {
      @Override
      public LearnerGraph MergeAndDeterminize(LearnerGraph original, StatePair pair) 
      {
        // Check that compatibility score computation gives the same response as if we did merge and computed a difference between the number of states.
        ScoreMode origScore = original.config.getLearnerScoreMode();original.config.setLearnerScoreMode(ScoreMode.COMPATIBILITY);
        long compatibilityScore = original.pairscores.computePairCompatibilityScore(pair);
        original.config.setLearnerScoreMode(origScore);
        LearnerGraph outcome = super.MergeAndDeterminize(original, pair);
        Assert.assertEquals(compatibilityScore+1,original.getStateNumber()-outcome.getStateNumber());
        return outcome;
      }


      @Override
      public Pair<Integer,String> CheckWithEndUser(
          @SuppressWarnings("unused")  LearnerGraph model,
          List<Label> question, @SuppressWarnings("unused") int valueForNoRestart,
          @SuppressWarnings("unused") List<Boolean> acceptedElements,
          @SuppressWarnings("unused") PairScore pairBeingMerged,
          @SuppressWarnings("unused")  final Object [] moreOptions)
      {
        Pair<Integer,String> oracleAnswer = new Pair<Integer,String>(expected.paths.tracePathPrefixClosed(question),null);
        return oracleAnswer;        
      }
    };
    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,testConfig,getLabelConverter()), buildSet(minus,testConfig,getLabelConverter())),expected.config);
    // Now do the same with ptasets instead of real sets
    PTASequenceSet plusPTA = new PTASequenceSet();plusPTA.addAll(buildSet(plus,testConfig,getLabelConverter()));PTASequenceSet minusPTA = new PTASequenceSet();minusPTA.addAll(buildSet(minus,testConfig,getLabelConverter()));
    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);
    /*
    if (null != WMethod.checkM(learntMachineNoRejects, expected))

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