Exemple #1
0
 public double dataLogLikelihood(InstanceList ilist) {
   double logLikelihood = 0;
   for (int ii = 0; ii < ilist.size(); ii++) {
     double instanceWeight = ilist.getInstanceWeight(ii);
     Instance inst = ilist.get(ii);
     Labeling labeling = inst.getLabeling();
     if (labeling != null)
       logLikelihood += instanceWeight * dataLogProbability(inst, labeling.getBestIndex());
     else {
       Labeling predicted = this.classify(inst).getLabeling();
       // System.err.println ("label = \n"+labeling);
       // System.err.println ("predicted = \n"+predicted);
       for (int lpos = 0; lpos < predicted.numLocations(); lpos++) {
         int li = predicted.indexAtLocation(lpos);
         double labelWeight = predicted.valueAtLocation(lpos);
         // System.err.print (", "+labelWeight);
         if (labelWeight == 0) continue;
         logLikelihood += instanceWeight * labelWeight * dataLogProbability(inst, li);
       }
     }
   }
   return logLikelihood;
 }
Exemple #2
0
 public double labelLogLikelihood(InstanceList ilist) {
   double logLikelihood = 0;
   for (int ii = 0; ii < ilist.size(); ii++) {
     double instanceWeight = ilist.getInstanceWeight(ii);
     Instance inst = ilist.get(ii);
     Labeling labeling = inst.getLabeling();
     if (labeling == null) continue;
     Labeling predicted = this.classify(inst).getLabeling();
     // System.err.println ("label = \n"+labeling);
     // System.err.println ("predicted = \n"+predicted);
     if (labeling.numLocations() == 1) {
       logLikelihood += instanceWeight * Math.log(predicted.value(labeling.getBestIndex()));
     } else {
       for (int lpos = 0; lpos < labeling.numLocations(); lpos++) {
         int li = labeling.indexAtLocation(lpos);
         double labelWeight = labeling.valueAtLocation(lpos);
         // System.err.print (", "+labelWeight);
         if (labelWeight == 0) continue;
         logLikelihood += instanceWeight * labelWeight * Math.log(predicted.value(li));
       }
     }
   }
   return logLikelihood;
 }