This function takes a DTM, phi matrix (P(word|topic)), and a theta matrix (P(topic|document)) and returns a single value for the likelihood of the data given the model.
CalcLikelihood(dtm, phi, theta, ...)
The document term matrix of class
The phi matrix whose rows index topics and columns index words. The i, j entries are P(word_i | topic_j)
The theta matrix whose rows index documents and columns index topics. The i, j entries are P(topic_i | document_j)
Other arguments to pass to
Returns an object of class
numeric corresponding to the log likelihood.
This function performs parallel computation if
dtm has more than 3,000
rows. The default is to use all available cores according to
However, this can be modified by passing the
cpus argument when calling