UMAP: Uniform Manifold Approximation and Projection
Leland McInnes, John Healy, Nathaniel Saul(Washington State University), Lukas Großberger(Radboud University Nijmegen)
Cited by 9,447Open Access
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.
Related Papers
No related papers found
Powered by citation graph analysis