public void Update(VariationalInferenceParameter varInference, CorpusDocument document)
{
for (int i = 0; i < CovarianceSufficientStatistic.RowCount; i++)
{
MuSufficientStatistic[i] = MuSufficientStatistic[i] + varInference.Lambda[i];
for (int j = 0; j < CovarianceSufficientStatistic.ColumnCount; j++)
{
double tmp = varInference.Lambda[i] * varInference.Lambda[j];
if (i == j)
{
CovarianceSufficientStatistic[i, j] = CovarianceSufficientStatistic[i, j] + varInference.Nu[i] + tmp;
}
else
{
CovarianceSufficientStatistic[i, j] = CovarianceSufficientStatistic[i, j] + tmp;
}
}
}
for (int i = 0; i < document.NbTerms; i++)
{
for (int j = 0; j < BetaSufficientStatistic.RowCount; j++)
{
var word = document.GetWord(i);
var count = document.GetCount(i);
BetaSufficientStatistic[j, word] = BetaSufficientStatistic[j, word] + count * varInference.Phi[i, j];
}
}
NData++;
}
public Bundle(int k, CorpusDocument document, LLNAModel model, VariationalInferenceParameter inference)
{
SumPhi = Vector <double> .Build.Dense(k - 1, 0);
Document = document;
Model = model;
VarInference = inference;
Init(k);
}
