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Corpus ID: 3641284

UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

@article{McInnes2018UMAPUM,
title={UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction},
author={L. McInnes and J. 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