clustersKmeans Ambiguity
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Description
I've got a question about the clustersKmeans function.
Normally, a K-means clustering algorithm assumes Euclidean space. Although, my understanding is that some libraries do have special options to account for the curvature of the earth.
Does your implementation of the K means algorithm do anything to adjust for the fact that the clustering occurs over a round surface? If so, it might be a good idea to specify this in the documentation.
Thank you.
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Research direction
Locate the clustersKmeans function and its existing documentation, then inspect how it measures distance and assigns points to clusters. Confirm whether the implementation accounts for Earth's curvature; done means documenting the actual behavior clearly, including any relevant limitations.
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Assessment
- Tech stack
- typescript
- Domain
- data
- Issue type
- Documentation
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100