kjaksic

Hi, I am joining the discussion since I would like to extract the average of document embeddings for topics, in order to compare similarities between the topics. If I understood...

@MaartenGr Thank you very much for the explanation and suggestion, will look into it!

@MaartenGr Is it expected behavior that the model extracted 569 topics, but the embedding matrix has a dimension of 570*384? Does this mean that the 0 index in the embedding...

Hi @MaartenGr , I have extracted the average document embedding for each topic using topic_model.topic_embeddings. Also, I estimated the average document embedding for each topic by calculating the average of...

@MaartenGr Thank you for such a detailed response! It is all clear.

Hi Maarten, Since inclusion of the time component (topics over time) in the model allows for the topic representation (top n words) to differ across the time, this should also...

Hi Marteen, thank you for the answer. Would it be possible to extract c-TF-IDF matrix at different time points and multiply it with word embeddings of keywords (as the topic...

@drob-xx Thank you! HDBSCAN implementation runs really fast. I indeed need DBCV to decide on optimal hyper-parameters (as one of the criteria). Thank you for those additional resources. Dealing with...

@drob-xx I agree with you that a decrease in the number of outliers does not necessarily mean that the model is better. That is why I am looking at the...

Great, sure, no problem. Thanks. On Thu, 15 Feb 2024 at 22:18, Matthew D. Cutone ***@***.***> wrote: > I'm fixing this issue for the next release. We don't have a...