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Description
Hello!
I seem to have encountered a memory overflow issue when using your UMP algorithm. My input is 26000 64 dimensional vectors, and metric uses cosine, n_ neighbors=8 and n_ components=2, When executing UMAP. fit_ transform(),there seems to have been a memory overflow error during transformer().
But n_ neighbors set larger, such as 25, so they can run normally
What's even more interesting is that another set of data with the same specifications did not show such an error. It's really strange. May I ask your opinion?
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Research direction
Start by reproducing the failure through UMAP.fit_transform() with 26,000 64-dimensional vectors, cosine distance, n_neighbors=8, and n_components=2. Compare it with n_neighbors=25 and the other dataset described, recording the complete memory error and where transformer() fails. Done means identifying a reproducible cause or documenting the missing conditions needed to diagnose it.
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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
- Needs clarification
- Newbie friendliness
- 25/100