Examples of trust.jfcm.learning.LearningConcept

trust.jfcm.learning.LearningConcept
This abstract class represents a generic learning method used for nodes within a fcm with a training mechanism @author t3 @version $Revision: 1.6 $

        
        if(c==null)
          System.err.println("Error: Concept "+e1.getConcept().getName()+" not found");
        
        
          LearningConcept lc = null;
          if(c instanceof LearningConcept)
            lc = (LearningConcept) c;
          
          if(lc != null && lc.isOutput()){
            OutputLearningConcept oc = (OutputLearningConcept) lc;
            System.out.println("  Output concept: "+c.getName());
            System.out.println("  Desirable output: "+oc.getDesirableOutput()+", output: "+oc.getOutput().doubleValue());
            System.out.println("  Error on output concept: "+c.getName()+": "+(oc.getDesirableOutput() - oc.getOutput().doubleValue()));

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      if(c==null)
        System.err.println("Error: Concept "+e1.getConcept().getName()+" not found");
      
      
        LearningConcept lc = null;
        if(c instanceof LearningConcept)
          lc = (LearningConcept) c;
        
        if(lc != null && lc.isOutput()){
          OutputLearningConcept oc = (OutputLearningConcept) lc;
          error += Math.pow(oc.getOutput() - e1.getValue(), 2);
          //System.out.println("  OutputNode: "+c.getName()+": "+c.getOutput()+", desirable value: "+e1.getValue());
        }

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      if(c==null)
        System.err.println("Error: Concept "+e1.getConcept().getName()+" not found");
      
      
        LearningConcept lc = null;
        if(c instanceof LearningConcept)
          lc = (LearningConcept) c;
        
        if(lc != null && lc.isOutput()){
          OutputLearningConcept oc = (OutputLearningConcept) lc;
          oc.setDesirableOutput(e1.getValue());
          //System.out.println("  OutputNode: "+c.getName()+": "+c.getOutput()+", desirable value: "+e1.getValue());
        }

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      Iterator<Concept> it = map.getConceptsIterator();
      while(it.hasNext()){
        Concept c = it.next();
        
        if(c instanceof LearningConcept){
          LearningConcept lc = (LearningConcept) c;
          if(!lc.isErrorCalculated()){
            
            
            
            
            //error to be calculated

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      WeightedConnection wconn = null;
      if(conn instanceof WeightedConnection)
        wconn = (WeightedConnection) conn;
      
      Concept cout = wconn.getTo();
      LearningConcept lout = null;
      if(cout instanceof LearningConcept)
        lout = (LearningConcept) cout;
      
      if(!lout.isErrorCalculated())
        /*
         * Error cannot be computed yet
         */
        return false;
      
      val += wconn.getWeight() * lout.getError();
      
    }
    
    /*
     * Set Error

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  private void setTrainingInputs(List<EntryStructure> inputs){
    for(int i=0; i<inputs.size(); i++){
      EntryStructure e1 = inputs.get(i);
      //System.out.println("EntryStructure: "+e1);
      
      LearningConcept lc = (LearningConcept) e1.getConcept();
      if(lc != null && lc.isInput()){
        InputLearningConcept ilc = (InputLearningConcept) lc;
        ilc.setInput(e1.getValue());
      }


    }

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    Iterator<Concept> it = map.getConcepts().values().iterator();
    while(it.hasNext()){
      Concept c = it.next();
        
      if(c instanceof LearningConcept){
        LearningConcept lc = (LearningConcept) c;
        Set<FcmConnection> out = lc.getOutConnections();
        Iterator<FcmConnection> it1 = out.iterator();
        
        while(it1.hasNext()){
          FcmConnection conn = it1.next();
          
          LearningWeightedConnection wconn = null;
          if(conn instanceof LearningWeightedConnection){
            wconn = (LearningWeightedConnection) conn;
            /*
             * Update learning connection
             */
            lc.getTrainingFunction().update(wconn);
          }
          
        }
          
      }

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  public void update(LearningWeightedConnection wconn) {
      double cWeight = wconn.getChangeInWeight();
      double weight = wconn.getWeight();
      double weightUncertainty = wconn.getWeightUncertainty();
      
      LearningConcept from = (LearningConcept) wconn.getFrom();
      double learnTimesError = learn * from.getError();
        
      /* Rule */
      //double delta = (learnTimesError * from.getOutput()) + (momentum * cWeight);
      
      double delta = 0;
      if(weight == weightUncertainty)
        delta = (learnTimesError * from.getOutput()) + (momentum * cWeight);
      else
        delta = (learnTimesError * weightUncertainty * from.getOutput()) + (momentum * cWeight);
      
      /*
      System.out.println("Connection: "+wconn);
      System.out.println("  learnTimesError: "+learnTimesError);
      System.out.println("  weightUncertainty: "+weightUncertainty);

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        if(c==null)
          System.err.println("Error: Concept "+e1.getConcept().getName()+" not found");
        
        
          LearningConcept lc = null;
          if(c instanceof LearningConcept)
            lc = (LearningConcept) c;
          
          if(lc != null && lc.isOutput()){
            OutputLearningConcept oc = (OutputLearningConcept) lc;
            logger.debug("");
            logger.debug("  Output concept: "+c.getName());
            logger.debug("  Desirable output: "+oc.getDesirableOutput()+", output: "+oc.getOutput().doubleValue());
            logger.debug("  Error on output concept: "+c.getName()+": "+(oc.getDesirableOutput() - oc.getOutput().doubleValue()));

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      if(c==null)
        System.err.println("Error: Concept "+e1.getConcept().getName()+" not found");
      
      
        LearningConcept lc = null;
        if(c instanceof LearningConcept)
          lc = (LearningConcept) c;
        
        if(lc != null && lc.isOutput()){
          OutputLearningConcept oc = (OutputLearningConcept) lc;
          error += Math.pow(oc.getOutput() - e1.getValue(), 2);
          //logger.debug("  OutputNode: "+c.getName()+": "+c.getOutput()+", desirable value: "+e1.getValue());
        }

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Related Classes of trust.jfcm.learning.LearningConcept

trust.jfcm.learning.supervised.LinearBP

trust.jfcm.learning.training.ForwardPropagation

trust.jfcm.learning.training.LinearRegression

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