Forcing exact high dimensional graph computation
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- Python
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Description
While performing some experiments and reading the code it seems for more than N(=4096) points the algorithm always does an approximate nearest neighbor search. Is there a way to force it to search for the exact nearest neighbors?
I don't want to pass the NxN matrix externally as I'd like to have the transform() functionality available.
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 tracing the transform() entry point and the N=4096 nearest-neighbor decision described in the issue. Determine the scope of supporting exact nearest-neighbor search without requiring an external NxN matrix; done means transform() remains available while using exact neighbors for high-dimensional inputs.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100