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I'm training a supervised model where I have (for example) 100 documents and 20 topics.
Some of the documents can have multiple topics assigned to them, moreover the documents cannot be split into sm…
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Hi Maarten,
you really built a very cool library here. Your work is very appreciated.
I am using Bertopic with River library's DBSTREAM as the cluster model. As online modeling isn't quite what I am…
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Hey Maarten,
Firstly thank you for all the help you have been uptill this point! 👍 👍 👍
I want to visualise the top topics using the same logic you so nicely showed here https://github.com/MaartenG…
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You do not give details on the indexes chosen in the comparison methods. From the runtime numbers, it appears that you did not add enable an index in ELKI? Do the runtimes include JVM startup cost, R …
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Hi Maarten,
I just have couple of questions-
1. After we fit and transform the model, it produces the main topic assigned to each document. If we find that theres a document (e.g. document 1) wh…
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Hi Maarten
I have been trying to get the sample docs from a topic model, below is the code up to the point where model is `.fit_transform`ed .
```
from sklearn.datasets import fetch_20newsgroup…
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hi Maarten,
I'm trying to train BERTopic with docs and extract top 30 documents with highest scores (descending order of doc_probs) for each topic as follows:
`doc_topics, doc_probs = topic_mode…
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Hello,
Thank you for this fantastic work, Bertopic is really useful. I was wondering why is the visualization of the hierarchy based off the results of the c_tf_idf ? Since the HDBSCAN results is …
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I am having trouble in extracting the gene list which belong to a specific cluster.
Is there a code or function which is already present to extract the genes?
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Hi Maarten, more than a problem it is a doubt.
What is the threshold of the probabilities to assign a register (a document) to a specific topic? That is, from what value in the probability of belo…