tslearn-team / tslearn-team/tslearn
KMeans question
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- Python
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Description
Hi, Thanks for the awesome library!
So I am running a Kmeans on lots of different datasets, which all have roughly four shapes, so I initialize with those shapes and it works well, except for just a few times. There are a few datasets that look different enough that I end up with empty clusters and the algorithm just hangs ("Resumed because of empty cluster" again and again).
I conceptually understand why this happens, but is there any way you know to avoid it, or finish at least? I'm not sure I understand what's going on behind the scenes well enough to debug any further. Thank you!
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
No file, test, or entry point is named. Start by reproducing the repeated “Resumed because of empty cluster” behavior with a representative dataset and inspect the KMeans implementation; done means identifying a reproducible way to avoid or terminate the empty-cluster loop and documenting or testing the agreed behavior.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100