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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. The algorithm is founded on three
assumptions about the data:
* The data is uniformly distributed on a Riemannian manifold;
* The Riemannian metric is locally constant (or can be approximated as such);
* The manifold is locally connected.
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