lmcinnes/umap

HNSW support

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#213 opened on Mar 25, 2019

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 (3 comments) (0 reactions) (0 assignees)Python (6,478 stars) (751 forks)batch import
help wanted

Description

Just curious if the HNSW algorithm is amenable to use in this project? Probably not directly because I see you are jitting in the distance metric but curious if it is worth a look into that algorithm for the nn search vs random projections? It is consistently the top performing algorithm on the ann shootout and I was wondering if the performance of UMAP is significantly impacted by the NN component and if so would incorporating HNSW make a meaningful difference?

Contributor guide

Tech stack
python
Domain
machine learningdata
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
4
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
over 1 week
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
unclear
Prerequisites
Knowledge of HNSW algorithmFamiliarity with UMAP internalsPython implementation skills
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
10
Research direction
Investigate the HNSW algorithm and its potential integration into UMAP's nearest neighbor search. Review existing HNSW implementations in Python (e.g., hnswlib) and assess compatibility with UMAP's distance metric optimization. Discuss with maintainers on whether this feature aligns with the project's goals. The issue currently lacks a clear implementation plan, so further discussion is required to define scope.
HNSW support · lmcinnes/umap#213 | Good First Issue