MaartenGr / MaartenGr/BERTopic
A metric is needed to reflect the quality of a model, just like the perplexity of LDA
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- Python
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Description
### Have you searched existing issues? 🔎
- [x] I have searched and found no existing issues
### Desribe the bug
After clustering, I couldn't find any indicators to verify my clustering results, but the LDA topic model has indicators such as perplexity that can verify the quality of the model. I need the same indicator in BERTopic, or do you have any alternative methods? Thank you very much
### Reproduction
```python
from bertopic import BERTopic
```
### BERTopic Version
0.16.4
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 minimal BERTopic import shown in the reproduction and review how BERTopic currently exposes topic-model results. Compare the requested quality indicator with LDA perplexity and define what “quality” should measure for BERTopic before proposing an evaluation approach.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100