Hi guys,
Recently I am trying to combine LDA(Latent Dirichlet Allocation) with some
clustering methods.
So I modified Matt Hoffman's onlineLDA to sklearn's format and use it with
other sklearn modules.
(I changed the input format to sparse matrix and speed up the e-step with
multiprocessing.)
I think it can be convenient to have some topic models in the package, but
I also find my work is very similar to gensim's LDA implementation.
So I want to ask how you guys think before I send a PR.
Any suggestions would be appreciated.
And if anyone is interested, my code is here: (It is pure python now. I am
trying to optimize it with cython.)
https://github.com/chyikwei/topicModels/blob/master/LDA/lda.py
example:
https://github.com/chyikwei/topicModels/blob/master/LDA/lda_example.py
Thanks,
Chyi-Kwei
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