问题
I am typical, regular, everyday R user. In R there is very helpful lda.collapsed.gibbs.sampler in lda package tha uses a collapsed Gibbs sampler to fit a latent Dirichlet allocation (LDA) model and returns point estimates of the latent parameters using the state at the last iteration of Gibbs sampling.
This function also has a great parameter compute.log.likelihood which, when set to TRUE, will cause the sampler to compute the log
likelihood of the words (to within a constant factor) after each sweep over the
variables. This is useful for assessing convergence and in comparing different LDA models (computeted for different number of topics).
I am interested if there is such an option in vowpal_wabbit's LDA model?
来源：https://stackoverflow.com/questions/31561067/how-to-compute-the-log-likelihood-of-the-lda-model-in-vowpal-wabbit