MaartenGr / MaartenGr/BERTopic
Online Clustering
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- Python
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Description
Hi @MaartenGr ,
I am trying to use Online topic modelling to solve my use-case. I am using RIVER(DBSTREAM) as mentioned in your help docs.
This DBSTREAM model of river package is a density-based algorithm, but it is not helping in finding the outliers in my dataset.
Assuming that my dataset has outlier, Is there any solution through which I can get outliers as well while using the above algorithm?
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 online topic-modelling help docs and River's DBSTREAM documentation mentioned in the issue. The request does not identify a file, entry point, or test; work would first need an agreed outlier-detection behavior and a reproducible dataset or test defining when the change is complete.
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
- 15/100