MaartenGr / MaartenGr/BERTopic
Persistent Zero Probability for Documents Previously Classified as Outliers after Implementing reduce_outliers and _map_probabilities
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- Python
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Description
Following the application of `topic_model.reduce_outliers` to minimize outliers and the subsequent updating of topic allocations probabilities with `_map_probabilities`, it is observed that documents which were initially classified as outliers (denoted by a topic of -1) and had a probability of zero, retain this zero probability post updating. This raises a question regarding whether this is an intended consequence of the operations, or if there may be a misunderstanding of the process involved.
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 by reading the implementations and documentation for topic_model.reduce_outliers and _map_probabilities, then trace how documents with topic -1 are handled across both operations. Reproduce the reported zero-probability behavior with a small outlier dataset and establish whether it matches the documented contract; completion requires a clear answer and, if incorrect, a regression test for the expected probabilities.
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
- Needs clarification
- Newbie friendliness
- 25/100