UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

McInnes, L., Healy, J., & Melville, J. (2018). UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. Journal of Open Source Software.

Type

Preprint

Intellectual base

Grey literature

Year

2018

Link

https://arxiv.org/abs/1802.03426

Cited from

mathematics, statistics_experimental_design

Cited by

2 citations across 2 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Dimension
  • UMAP

    This sourceNonlinear manifold dimensionality reduction grounded in Riemannian geometry and algebraic topology, balancing local and global structure.

• Dimensionality Reduction
  • A national specialty retail chain with approximately 4 million active loyalty members rebuilt customer segmentation using dimensionality reduction

    This sourceUMAP topological-preservation method; supports marker 073 (multi-stage PCA→UMAP→HDBSCAN customer-segmentation pipeline).

Verification

This reference passed the adversarial substantiation pipeline: it was checked to exist and to support the claim it is attached to. See how references were verified.

Registry ID ref:7f1b8ad3f874 · see in the full table