• Mathematics, Computer Science
  • Published in ArXiv 2018

UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

@article{McInnes2018UMAPUM,
  title={UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction},
  author={Leland McInnes and John Healy},
  journal={ArXiv},
  year={2018},
  volume={abs/1802.03426}
}
UMAP (Uniform Manifold Approximation and Projection) is a novel manifold learning technique for dimension reduction. UMAP is constructed from a theoretical framework based in Riemannian geometry and algebraic topology. The result is a practical scalable algorithm that applies to real world data. The UMAP algorithm is competitive with t-SNE for visualization quality, and arguably preserves more of the global structure with superior run time performance. Furthermore, UMAP as described has no… CONTINUE READING

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