Closed koheiw closed 4 years ago
If you see the code of topicmodels, you will understand why. I also though that its implementation of seeded LDA is wrong. However, I am happy to make this a separate package.
I have seen it and it's a mess, so is the package. We could offer a simpler approach, so I didn't want to give the impression that I am totally against it, just aware of some challenges. Can we meet those challenges by simplifying the post-estimation functions in a simpler, quanteda-like way, and/or allow them to work with those already found in another package such as stm, or the excellent LDAvis?
No worries. I was aware that topicmodels has the seeded LDA. This is exactly why I chose LDAGibbs++ here. I am only interested semisupervided LDA so unsupervised LDA is just an by product. The library has many more functions for online training and prediction on new data, but you remained me that I have to work a lot to add functions that I have no plan to use if I add the code to this package. This is why I am happy to put that in my seededlda package (which is currently depends on topicmodels).
Ah, users, we love them but they always ask for more. https://github.com/bstewart/stm/issues
We don't have enough resources to maintain so many functions, so we need let users to develop the packages via PR. This is why I think modularization is urgently needed.
Maybe it would be an option to participate in the Hacktoberfest event. I tried to participate last year but there were almost no R
issues around to solve.
@JBGruber can you tell how we can make you (or people like you) feel like to contribute quanteda.textmodels or quanteda actively?
I think the Hacktoberfest guidelines for maintainers are a pretty good starting point to get people to contribute actively:
So I think to get people to help you would have to communicate that you want help and for what specifically. That's why I brought up the Hacktoberfest. But you could also, for example, organise a quanteda-hackaton to solve a long list of issues at once to get things going. I would show up :wink:
Address #30