MaartenGr / MaartenGr/BERTopic
Fewer topics than the number of articles
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- Python
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Description
Hi, I am using the partial_fit function to generate topics continuously. However at some batches the number of topics could be a bit fewer than the number of articles in the dataset. I have checked the "labels" attribute in "partial_fit" and it returns exactly the same topics as articles, but when I called "model.topics_" after BERTopic it returns fewer topics. How could this happen and what can I do to solve it? Or at least, can I know which articles did not get assigned a topic? I can drop them directly as there are usually only 2 or 3 articles with missing topics. Thanks!
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First steps
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Research direction
Start by reproducing the reported behavior with BERTopic.partial_fit, comparing its labels attribute with model.topics_ after processing batches. Read the partial_fit and topics_ entry points referenced in the issue, then determine why articles may be missing and how those articles can be identified; done means a documented explanation or a verified fix with regression coverage.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100