MaartenGr / MaartenGr/BERTopic
I found my topic reprensentation changed after using reduced outlier
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- Python
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Description
I found the my topic representation changed from meaningful words(the topic I want to see) to the useless words(the, of, and...) after using the reduced outlier function.
code is look like this:
new_topics = topic_model.reduce_outliers(self.docs, topics, strategy="distributions")
topic_model.update_topics(self.docs, topics=new_topics)
representative_docs = topic_model.get_representative_docs()
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the reported calls to reduce_outliers, update_topics, and get_representative_docs, and reproduce the change using the example code and documents. Compare the topic representations before and after reduction and determine whether meaningful terms are lost; done means the behavior is explained and a focused regression test or fix is identified.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100