The Journal of Open Source Software· 2018
UMAP: Uniform Manifold Approximation and Projection
- 9,692citations
- 2018year
Short summary
UMAP is a new dimension reduction technique offering both visualization and general non-linear reduction capabilities, built on a rigorous mathematical foundation but with a user-friendly API.
AI-generated from the title and abstract; the full text is not read.
Key points
- UMAP provides both visualization and general non-linear dimension reduction.
- It is built on a rigorous mathematical foundation.
- UMAP features a simple, scikit-learn compatible API.
- It is significantly faster than most t-SNE implementations.
AI-generated from the title and abstract; the full text is not read.
Abstract
Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t-SNE, but also for general non-linear dimension reduction. UMAP has a rigorous mathematical foundation, but is simple to use, with a scikit-learn compatible API. UMAP is among the fastest manifold learning implementations available -significantly faster than most t-SNE implementations.
The authors' abstract, as published at the source. The Journal of Open Source Software, 2018 · DOI ↗
Continue with a free account
Ask the paper: 3 free questions a day about this paper; save it, get its citation, new summaries every day for your field. Takeaways are Premium.
Continue free on the webSign in with Google or Apple; no card needed. You come back to this paper.
On your phone:
Field: Computational Mechanics
Computational MechanicsEngineering