Separate distincts clouds
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- Dominant language
- Python
- Stars
- 8.3k
- Forks
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- Avg merge
- 1d 13h
- Merged PRs (30d)
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Description
Currently, I have two distinct clounds, but they are stick together.
Is there a way to separate them with UMAP? Otherwise, what could be a good alternative to separate them topologically? Is there an analytic approach which can be used here?
**UPDATE**
I am looking for an analytical approach to separate the clouds after applying umap.fit_transform(). I used different approach to get distinct clouds with t-SNE, PCA, SVM, used NN to classify the points. The problem is I always got clouds stick together. The better result though was with UMAP. Now, I am interested to force to separate the clouds once the UMAP has been applied.
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
The issue provides no file, test, or entry point to begin from; start by locating the UMAP transform implementation and its existing tests. Done would require a maintainer-approved analytical approach for separating the resulting clouds, together with tests or documented evidence that the approach works.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data-visualization, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 18/100