I'm reading a paper Gibbs sampling for the uninitiated.
In this paper, the authors try to use Gibbs sampling for a bayesian naive bayes model. They formalize the model as a graphical model in page 8. And in the example, they are trying to predict the emotion(sentiment) of a document.
However, what I don't understand is that, they claim without label $L$, using Gibbs sampling could still sample all the parameters needed, including $L$. I'm not sure how should I interpret this. Without training label, it's essentially a clustering problem, but if not using labels, how should we interpret the learnt label $L$?
Thanks in advance.