dillondaudert/UMAP.jl
Uniform Manifold Approximation and Projection (UMAP) implementation in Julia
This tool helps data scientists and analysts simplify complex, high-dimensional datasets for easier visualization and pattern identification. You input your raw data, potentially along with a pre-calculated distance matrix, and it outputs a lower-dimensional representation (an 'embedding') that preserves the essential relationships within your data. This makes it easier to spot clusters or trends that would be invisible in the original high-dimensional space.
144 stars.
Use this if you need to reduce the complexity of large datasets to visualize underlying structures or prepare them for other analyses.
Not ideal if your primary goal is precise, interpretable feature selection rather than visual exploration or general data simplification.
Stars
144
Forks
17
Language
Julia
License
MIT
Category
Last pushed
Feb 04, 2026
Commits (30d)
0
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