@Override
public double calculate_E_step(_Doc d) {
// Step 1: pre-compute emission probability
if (m_collectCorpusStats) // indicates this is training
ComputeEmissionProbsForDoc(d);
// Step 2: use forword/backword algorithm to compute the posterior
double logLikelihood = m_hmm.ForwardBackward(d, emission);
// Step 3: collection expectations from the posterior distribution
m_hmm.collectExpectations(p_dwzpsi); // expectations will be in the original space
accTheta(d);
estThetaInDoc(d); // get the posterior of theta
if (m_collectCorpusStats) {
accEpsilonStat(d);
accSigmaStat(d);
accPhiStat(d);
}
return logLikelihood + docThetaLikelihood(d);
}
int[] get_MAP_topic_assignment(_Doc d) {
int path[] = new int[d.getSenetenceSize()];
m_hmm.BackTrackBestPath(d, emission, path);
return path;
}
