Vikash Singh

Ok.. cool.. let me see how I can incorporate that in the main code. If that works better then we can switch to this approach all together.. Thanks for the...

@cassiehkx can you share link to some other form of LDA which has `incremental learning` or any other library? Basically I want to understand how that works so I can...

Fair point, switching to sparse matrix should be easier in comparison to incremental learning.

Hey Dipin, I think when we seed topics we provide the topic id to the words/terms. This should help us figure out the seeded topics and the non seeded ones....

Got it, thanks :) On Wed, Apr 24, 2019 at 10:59 AM Yuan Chen wrote: > In guidedlda/guidedlda.py, for class GuidedLDA, you have: > > alpha : float, default 0.1...

@gam-ba What is the `seed_confidence` value you are using at the fit step? ``` model.fit(X, seed_topics=seed_topics, seed_confidence=0.15) ```

Ideally if you are getting good results for lower value of seed_confidence, then you should try without seeding as well. Try the other fit method and see how that works...

Hi Vnnw, Thanks for sharing, but there is no such method implemented as of now. It would be awesome to have it, but it's missing currently. :(

Hey Lucy, The model currently supports only a symmetric prior. I know how useful an asymmetric prior can be, sorry it's not there as of now :( Vikash

Hi, No this is not under development anymore. Regards, Vikash On Thu, May 23, 2019 at 5:48 PM Salah Hassanin wrote: > Hey Lucy, > > The model currently supports...