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;
}
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;
}