public static void reportTrainingLikelihood (ACRF acrf, InstanceList trainingList) { double total = 0; Inferencer inf = acrf.getInferencer (); for (int i = 0; i < trainingList.size (); i++) { Instance inst = trainingList.get (i); ACRF.UnrolledGraph unrolled = acrf.unroll (inst); inf.computeMarginals (unrolled); double lik = inf.lookupLogJoint (unrolled.getAssignment ()); total += lik; logger.info ("...instance "+i+" likelihood = "+lik); } logger.info ("Unregularized joint likelihood = "+total); }
public static void reportTrainingLikelihood (ACRF acrf, InstanceList trainingList) { double total = 0; Inferencer inf = acrf.getInferencer (); for (int i = 0; i < trainingList.size (); i++) { Instance inst = trainingList.get (i); ACRF.UnrolledGraph unrolled = acrf.unroll (inst); inf.computeMarginals (unrolled); double lik = inf.lookupLogJoint (unrolled.getAssignment ()); total += lik; logger.info ("...instance "+i+" likelihood = "+lik); } logger.info ("Unregularized joint likelihood = "+total); }
public static void reportTrainingLikelihood (ACRF acrf, InstanceList trainingList) { double total = 0; Inferencer inf = acrf.getInferencer (); for (int i = 0; i < trainingList.size (); i++) { Instance inst = trainingList.get (i); ACRF.UnrolledGraph unrolled = acrf.unroll (inst); inf.computeMarginals (unrolled); double lik = inf.lookupLogJoint (unrolled.getAssignment ()); total += lik; logger.info ("...instance "+i+" likelihood = "+lik); } logger.info ("Unregularized joint likelihood = "+total); }
Inferencer inf = acrf.getInferencer (); inf.computeMarginals (unrolled);
Inferencer inf = acrf.getInferencer (); inf.computeMarginals (unrolled);
Inferencer inf = acrf.getInferencer (); inf.computeMarginals (unrolled);