Hello Gensim Team,
Thanks for the amazing package and support you provide, it is invaluable to us lowly researchers who use your tools.
I am estimating an Author Topic model and after the model has converged, I want to retrieve the final values for the hyper parameters. I want the (num of authors * num topics) gamma matrix and the (num of topics * num tokens) lambda matrix. (My ultimate goal is to build the entire (d * v * a *k) phi matrix, but have decided given that you use the Lee, Seung: “Algorithms for non-negative matrix factorization”, NIPS 2001
. approach, it will be easier to get the gammas and lambdas and calculate phi given the optimised values )
Just as a note, I have read over the conversation called "difference between lda.expElogbeta and lda.show_topics ?" but that is from 2013 and the content appears not to be applicable now, if I am wrong about that my apologies.
My question is simply how can I retrieve both matrices gamma and lambda after convergence?
I have been playing around with
gamma, stats = model.inference(corpus, dictionary, author2doc, doc2author, rhot, collect_sstats=True)
where I set rhot to the final value pre-convergence listed in the log file. But I get a gamma matrices where the number of rows does not match the number of authors in the corpus. I am loading the entire corpus as one chunk.
Forgive my ignorance, but if there are any materials or previous examples I could go over that would be amazing.