A primarily internal function for calculating words according to the score metric.
We expect most users will use labelTopics
instead.
calcscore(logbeta)
a K by V matrix containing the log probabilities of seeing word v conditional on topic k
Score is a metric which we include because it is used effectively in the lda package by Jonathan Chang. It is calculated as: $$\beta_{v, k} (\log \beta_{w,k} - 1 / K \sum_{k'} \log \beta_{v,k'})$$
Jonathan Chang (2015). lda: Collapsed Gibbs Sampling Methods for Topic Models. R package version 1.4.2. https://CRAN.R-project.org/package=lda
labelTopics