I imagine LDA and related models would be welcome additions to
scikit-learn. However, Hoffman's work has a GPL license so it cannot be
included in scikit-learn (or else scikit-learn would have to be distributed
under GPL). Your API-adapted version is nonetheless useful for individuals
seeking a scikit-learn compatible LDA model who do not intend to distribute
the system.
- Joel
On Thu, Oct 31, 2013 at 6:19 PM, Eustache DIEMERT <eusta...@diemert.fr>wrote:
> This sounds very interesting !
>
> Plus it seems you already embraced sklearn's API in this module.
>
>
> 2013/10/31 chyi-kwei yau <chyikwei....@gmail.com>
>
>> 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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